To take advantage of these content-based functionalities , video sequences must be segmented into semantically meaningful objects . Video object segmentation is a key step in defining the content of any video sequences . The algorithm proposed in this paper is a spatiotemporal segmentation . Video object segmentation entails selecting and extracting objects of interest from a video sequence . Video Segmentation of Objects ( VSO ) is a critical task which has many applications , such as video edit , video decomposition and object recognition . The major enabling technology for the MPEG-4 standard are systems that compute video object segmentation , i.e. , the extraction of video objects from a given video sequence . Our surface optimization formulation describes the video object segmentation problem in the form of an energy function that integrates many visual processing techniques . By optimizing this surface , we balance visual information against predictions of models with a priori information and extract video objects from a video sequence . So long as objects move sufficiently with respect to the viewer at some point , they will be detected and subsequently tracked for the rest of the video . We evaluated our approach on the video object segmentation problem . The resulting system has the capability to automatically discover objects from occlusions in video and track their shapes as they evolve over time . This paper proposes a real-time scheme for object segmentation in video . In the first stage a segmentation based on pairwise region comparison is utilized to oversegment image through extracting superpixels . Further embedding of the PHMM parameters captures the long term spatial dependencies on a shape profile , hence the global characteristics of a shape class . ( 3 ) We incorporate the proposed methods in a spatio-temporal MRF model to solve the video-based object segmentation problem . Our new model is a simultaneous object segmentation , background modeling , and pose estimation framework , which combines the top-down high-level object shape constraints with the bottom-up low-level image cues , and features a flexible graph structure induced by the motion information for more reliable temporal smoothness . The current research project proposes advanced statistical and adaptive threshold techniques for video object detection and segmentation . We present new statistical adaptive threshold techniques to show the advantages , and how these algorithms overcome the limitations and the technical challenges for object motion detection . Evaluation metrics are the essential element in performance evaluation methodology . Recent works on video object segmentation/extraction are mostly restricted to a single objective metric to judge the overall performance of algorithms . Motivated by a novel framework for performance evaluation on image segmentation using Pareto front , we propose a multi-metric evaluation protocol , including metrics for contour-based spatial matching , temporal consistency , user workload and time consumption . From a video object segmentation perspective , using a joint spatio-temporal strategy is superior to processing with priority in either the spatial or temporal domains , as it considers a video sequence as a spatio-temporal grouping of pixels . However , existing spatio-temporal object segmentation techniques consider only pixel features , which tend to limit their performance in being able to segment arbitrary shaped objects . The method comprises the steps : respectively storing video data in local storage space of video broadcasting nodes ; and converting the video data into YUV ( Luma and Chroma ) image sequences respectively by the video broadcasting nodes . The YUV image sequence is arranged by frames in a one-to-one manner , the video can be synchronously corrected to each frame when the video data is broadcast , thereby being more precise in video synchronization compared with the existing video broadcasting progress time ; in addition , the video data is stored in the local storage space corresponding to the video broadcasting nodes , so that the image mislocation , tearing , color breaking and the like caused by the low data transmission efficiency can also be effectively avoided , and a better video synchronization effect can be realized . This work addresses the video synchronization problem , which consists in finding the temporal alignment between sequences of images acquired with unsynchronized cameras . This problem has been addressed before , under the assumptions that the cameras are static or jointly moving and that there are correspondences between the features visible in the different sequences . Video sequence synchronization is often necessary for computer vision applications where multiple simultaneously recorded videos are processed . We present a coarse-to-fine approach to synchronizing two video sequences recorded at the same frame rate by stationary cameras with fixed internal parameters . To ensure robustness , an automated calibration system has been developed that ensures the pixels are correctly mapped . Video frame synchronization is also developed . Graftek 's software layer drives an Image Grabber board from Neotech ( Eastleigh , United Kingdom ) . A Colour Adapter box from Neotech provides adequate video signal synchronization . The system also requires a LabVIEW driven digital output board ( MacADIOS II from GW Instruments , Cambridge , MA ) controlling a slightly modified VCR remote control used mainly to advance the video tape frame by frame . The system video interface offers user selectable 320 x 200 , 640 x 480 , 768 x 480 or 1280 x 400 resolution with a displayable palette of 4,096 colors and interlaced , noninterlaced and overscan modes . NTSC compatibility permits simple and inexpensive video signal synchronization , so that composed monitor images can be displayed and recorded with standard video equipment . The processor , in conjunction with the custom video chips , can manipulate models mathematically at a sufficient rate to present moving or animated images in real time . Video synchronization and alignment is a rather recent topic in computer vision . It usually deals with the problem of aligning sequences recorded simultaneously by static , jointly- or independently-moving cameras . After the implementation of this project , the video characteristics were evaluated using likert scale . Analysis of 30 user responses indicated that 17 users ( 56.7 percent ) rated the image quality as excellent , the video and image synchronization was rated as excellent by 9 users ( 30 percent ) , the Background noise was rated excellent by 18 users ( 60 percent ) , the Character Impression was rated Excellent by 11 users ( 36.67 percent ) , the general assessment of the storyline was rated excellent by 17 users ( 56.7 percent ) , the video Impression was rated excellent by 11 users ( 36.67 percent ) and the voice quality was rated by 10 users ( 33.33 percent ) as excellent . Through sending time stamp updating information to the normal nodes , the center node controls play progress of the normal nodes . The invention relates to video data extraction , video data block distribution and video synchronization play . The method in the invention has high file transmission rate , and user experience pleasure is increased . The method includes the steps that an ultrahigh-resolution video source is divided into equal small videos to be placed on different node computers , and the identical frames of all the small videos are marked by an identical serial number ; a main control computer connected with a camera sends commands to all the node computers to enable all the node computers to start to play the videos at the same time ; the camera starts to photograph the whole video frames synchronously , and whether the series numbers of all the frames are consistent is analyzed ; when the serial numbers of certain frames are inconsistent , the main control end sends commands to the node computers with the frames inconsistent to modify the refresh rates of the node computers , and the refresh rates are modified continuously until the serial numbers of the frames of all the node computers reaching the identical frames are consistent . According to the method , the serial numbers of the whole frames of the videos are photographed through the camera and judged whether to be consistent or not and then judged whether to perform video synchronization processing or not , and thus manual intervention is reduced ; communication can be carried out without a network , the multi-computer synchronization problems caused by network communication abnormality and network response abnormality are greatly reduced . in de-interlacing algorithms are fundamental to explore image quality potential on modern TV screen technologies . This paper presents a true motion vector verification algorithm based on multi temporal block matching strategy , applied to video de-interlacing . During field scanning , a block of pixels is selected , then a block with the same reference coordinates is extracted but in the future field . Despite these algorithms are developed using software implementations , their implementations in hardware are required to achieve real-time operation . This paper describes the development of an embedded system for video de-interlacing . The algorithm for video de-interlacing uses three fuzzy logic-based systems to tackle three relevant features in video sequences : motion , edges , and picture repetition . Ethernet passive optical networks ( EPONs ) are designed to deliver services for numerous applications such as voice over Internet protocol , standard and high-definition video , video conferencing ( interactive video ) , and data traffic . Various dynamic bandwidth allocation and intra-optical network unit ( ONU ) scheduling algorithms have been proposed to enable EPONs to deliver differentiated services for traffic with different quality of service ( QoS ) requirements . A mobile terminal equipped with multiple interfaces can achieve a much higher bandwidth by aggregating the bandwidth offered by the individual networks . This helps support demanding applications like interactive video . Often , in spite of bandwidth aggregation , the available bandwidth may be too small to avoid frame loss altogether . This invention relates to a video interfacing arrangement and MPEG media type for connecting at least one display device , for example a screen-like device of television , at least one video source , consisting essentially of First , a processing unit adapted to display any type of MPEG video streams in real time or delayed , store , save and / or sent over a broadcast network ( 4 ) and / or over a wide area telecommunication network ( 10 ) and , secondly , at least one screen interface ( 7 ) and a connection interface to a local or wide area network ( 5 , 9 ) , characterized in that it comprises essentially one hand , a memory of certain B and P pictures in each audiovisual portal ( 12 ) and secondly , that each arrangement of video interfacing ( 8) has storage , recording and processing audiovisual program and is associated with at least one device screen type display television ( 6 ) , each arrangement of video interfacing ( 8) reconstructing the MPEG stream from the information of its own hard drive and algorithms and B and P pictures from the portal ( 12 ) . In this thesis we address each of the three issues and make some original contributions . These include a new method of analyzing multidimensional filter banks ; a general technique of transforming filter banks from one dimension to another ; a complete structure for one-dimensional perfect reconstruction filter banks , which can also be used to synthesize multidimensional filter banks as well as multidimensional linear phase filter banks ; an analysis of interlaced video and applying some of the above concepts in coding of interlaced video , in particular in a multiresolution or scalable manner . The algorithm also works well for scene change condition . Test results for coding interlaced video ( 720 x576 PAL ) are reported . Interlaced video acquisition and transmission , used as a simple way of increasing motion quality in video sequences , all by respecting the bandwidth constraints of progressive format representation , has been extensively used by analogue transmission systems . However , considering that nowadays the television sets and the flat screens can display only progressive format input , ensuring a smooth and high quality interlaced to progressive format conversion represents a challenging task . Hence , the structure that gives the easiest implementation can be chosen . The spatial domain structure is preferred for motion compensation and for line interlaced video signals . Interframe hybrid coding experiments are performed on interlaced videophone scenes using an adaptive transform coder . Based on Finite Automata and Conceptual Graphs , this formalism allows to express spatial and temporal constraints , as to define sequences of events in a video and positions of objects in an image . In addition to the description of complex concepts , this formalism allows to monitor behaviors in a video-surveillance context , to detect important highlights in a sport context and also to validate MPEG7-based descriptions . The high-performance video coding is activated as a research project of the ISO/IEC Moving Picture Experts Group in the year 2008 , and a new standardization is already under discussion and preparation . This paper gives a brief introduction to the development of this project and an overview of the related concepts and technologies . The key to high-performance video coding lies in an efficient reduction of the temporal redundancies . For this purpose , motion estimation and compensation techniques have been successfully applied . Besides , approaches to en- code the statistics of sequential binary data in the manifold of statistical models are proposed , resulting in the bag-of-words for attribute dynamics ( BoWAD ) and vector of locally aggregated descriptor for attribute dynamics (VLADAD).Empirical study on challenging tasks of complex human activity analysis justifies the effectiveness of the proposed framework . Our solution not only produces the state-of-the-art results for event detection , but also enables recount- ing that provides the visual evidence anchored over time in the video for the prediction , and facilitates tasks like semantic video segmentation , content based video summarization , and so forth . A kD-tree-based nearest-neighbour search strategy is employed to accelerate the search procedure . Experimental results show that our method is computationally efficient and practically effective to build a content-based video summarization system . Query-by-example video retrieval is receiving an increasing attention in recent years . One of the state-of-art approaches is the Bag-of-visual Words ( BoW ) based technique , where images are described by a set of local features mapped to a discrete set of visual words . The " Bag of Visual Words " ( BoW ) framework has been widely used in query-by-example video retrieval to model the visual content by a set of quantized local feature descriptors . In this paper , we propose a novel technique to enhance BoW by the selection of Word-of-Interest ( WoI ) that utilizes the quantified temporal motion coherence of the visual words between the adjacent frames in the query example . Keywords : Media Video Learning , Report Writting , Model Development . Multicast addressing was chosen over the broadcast address and unicast address mechanisms for the transmission of video data over the LAN . Dynamic allocation of multicast addresses enables such features as the continuous playback of full motion video over a network with multiple viewers . Design of this video data transmission system permits interested nodes on a LAN to dynamically allocate a single multicast address from a pool of multicast addresses . In this paper , we consider the challenging problem of object duplicate detection and localization . Several applications require efficient object duplicate detection methods , such as automatic video and image tagging , video surveillance , and high level image or video search . In this paper , a novel graph-based approach for 3D object duplicate detection in still images is proposed . To provide a further “ taste ” of multimedia , we show how simple animations may proceed . To round out the discussion of such tasks , we consider a “ build your own ” video-transition problem , where the intent would be to generate one ’s own video transition . We then go on to review the current and future state of multimedia sharing and distribution , outlining later discussions of social media , video sharing , and new forms of TV . Methods and systems for identifying video clips in a video clip repository that are of the same event are disclosed . Video clips are identified as being of the same event based on timestamps and geolocation stamps associated with the video clips . However , limited by the scale of available surveillance video datasets , few existing human analysis approaches report their performances on such complex events . To this end , we present a new large-scale dataset , named Human-in-Events or HiEve ( human-centric video analysis in complex events ) , for understanding human motions , poses , and actions in a variety of realistic events , especially crowd & complex events . It contains a record number of poses ( > 1 M ) , the largest number of action labels ( > 56k ) for complex events , and one of the largest number of trajectories lasting for long terms ( with average trajectory length > 480 ) . Visual Question Answering ( VQA ) is an emerging interdisciplinary research problem at the intersection of computer vision , natural language processing and artificial intelligence . It has many real - life applications , such as automatic querying of surveillance video or assisting the visually impaired . Compared to the recently popular image captioning task , VQA requires a deeper understanding of the image , but is considerably easier to evaluate .
To take advantage of these content-based functionalities , video sequences must be segmented into semantically meaningful objects . Video object segmentation is a key step in defining the content of any video sequences . The algorithm proposed in this paper is a spatiotemporal segmentation .
Video object segmentation entails selecting and extracting objects of interest from a video sequence . Video Segmentation of Objects ( VSO ) is a critical task which has many applications , such as video edit , video decomposition and object recognition .
The major enabling technology for the MPEG-4 standard are systems that compute video object segmentation , i.e. , the extraction of video objects from a given video sequence . Our surface optimization formulation describes the video object segmentation problem in the form of an energy function that integrates many visual processing techniques . By optimizing this surface , we balance visual information against predictions of models with a priori information and extract video objects from a video sequence .
So long as objects move sufficiently with respect to the viewer at some point , they will be detected and subsequently tracked for the rest of the video . We evaluated our approach on the video object segmentation problem . The resulting system has the capability to automatically discover objects from occlusions in video and track their shapes as they evolve over time .
This paper proposes a real-time scheme for object segmentation in video . In the first stage a segmentation based on pairwise region comparison is utilized to oversegment image through extracting superpixels .
Further embedding of the PHMM parameters captures the long term spatial dependencies on a shape profile , hence the global characteristics of a shape class . ( 3 ) We incorporate the proposed methods in a spatio-temporal MRF model to solve the video-based object segmentation problem . Our new model is a simultaneous object segmentation , background modeling , and pose estimation framework , which combines the top-down high-level object shape constraints with the bottom-up low-level image cues , and features a flexible graph structure induced by the motion information for more reliable temporal smoothness .
The current research project proposes advanced statistical and adaptive threshold techniques for video object detection and segmentation . We present new statistical adaptive threshold techniques to show the advantages , and how these algorithms overcome the limitations and the technical challenges for object motion detection .
Evaluation metrics are the essential element in performance evaluation methodology . Recent works on video object segmentation/extraction are mostly restricted to a single objective metric to judge the overall performance of algorithms . Motivated by a novel framework for performance evaluation on image segmentation using Pareto front , we propose a multi-metric evaluation protocol , including metrics for contour-based spatial matching , temporal consistency , user workload and time consumption .
From a video object segmentation perspective , using a joint spatio-temporal strategy is superior to processing with priority in either the spatial or temporal domains , as it considers a video sequence as a spatio-temporal grouping of pixels . However , existing spatio-temporal object segmentation techniques consider only pixel features , which tend to limit their performance in being able to segment arbitrary shaped objects .
The method comprises the steps : respectively storing video data in local storage space of video broadcasting nodes ; and converting the video data into YUV ( Luma and Chroma ) image sequences respectively by the video broadcasting nodes . The YUV image sequence is arranged by frames in a one-to-one manner , the video can be synchronously corrected to each frame when the video data is broadcast , thereby being more precise in video synchronization compared with the existing video broadcasting progress time ; in addition , the video data is stored in the local storage space corresponding to the video broadcasting nodes , so that the image mislocation , tearing , color breaking and the like caused by the low data transmission efficiency can also be effectively avoided , and a better video synchronization effect can be realized .
This work addresses the video synchronization problem , which consists in finding the temporal alignment between sequences of images acquired with unsynchronized cameras . This problem has been addressed before , under the assumptions that the cameras are static or jointly moving and that there are correspondences between the features visible in the different sequences .
Video sequence synchronization is often necessary for computer vision applications where multiple simultaneously recorded videos are processed . We present a coarse-to-fine approach to synchronizing two video sequences recorded at the same frame rate by stationary cameras with fixed internal parameters .
To ensure robustness , an automated calibration system has been developed that ensures the pixels are correctly mapped . Video frame synchronization is also developed .
Graftek 's software layer drives an Image Grabber board from Neotech ( Eastleigh , United Kingdom ) . A Colour Adapter box from Neotech provides adequate video signal synchronization . The system also requires a LabVIEW driven digital output board ( MacADIOS II from GW Instruments , Cambridge , MA ) controlling a slightly modified VCR remote control used mainly to advance the video tape frame by frame .
The system video interface offers user selectable 320 x 200 , 640 x 480 , 768 x 480 or 1280 x 400 resolution with a displayable palette of 4,096 colors and interlaced , noninterlaced and overscan modes . NTSC compatibility permits simple and inexpensive video signal synchronization , so that composed monitor images can be displayed and recorded with standard video equipment . The processor , in conjunction with the custom video chips , can manipulate models mathematically at a sufficient rate to present moving or animated images in real time .
Video synchronization and alignment is a rather recent topic in computer vision . It usually deals with the problem of aligning sequences recorded simultaneously by static , jointly- or independently-moving cameras .
After the implementation of this project , the video characteristics were evaluated using likert scale . Analysis of 30 user responses indicated that 17 users ( 56.7 percent ) rated the image quality as excellent , the video and image synchronization was rated as excellent by 9 users ( 30 percent ) , the Background noise was rated excellent by 18 users ( 60 percent ) , the Character Impression was rated Excellent by 11 users ( 36.67 percent ) , the general assessment of the storyline was rated excellent by 17 users ( 56.7 percent ) , the video Impression was rated excellent by 11 users ( 36.67 percent ) and the voice quality was rated by 10 users ( 33.33 percent ) as excellent .
Through sending time stamp updating information to the normal nodes , the center node controls play progress of the normal nodes . The invention relates to video data extraction , video data block distribution and video synchronization play . The method in the invention has high file transmission rate , and user experience pleasure is increased .
The method includes the steps that an ultrahigh-resolution video source is divided into equal small videos to be placed on different node computers , and the identical frames of all the small videos are marked by an identical serial number ; a main control computer connected with a camera sends commands to all the node computers to enable all the node computers to start to play the videos at the same time ; the camera starts to photograph the whole video frames synchronously , and whether the series numbers of all the frames are consistent is analyzed ; when the serial numbers of certain frames are inconsistent , the main control end sends commands to the node computers with the frames inconsistent to modify the refresh rates of the node computers , and the refresh rates are modified continuously until the serial numbers of the frames of all the node computers reaching the identical frames are consistent . According to the method , the serial numbers of the whole frames of the videos are photographed through the camera and judged whether to be consistent or not and then judged whether to perform video synchronization processing or not , and thus manual intervention is reduced ; communication can be carried out without a network , the multi-computer synchronization problems caused by network communication abnormality and network response abnormality are greatly reduced .
in de-interlacing algorithms are fundamental to explore image quality potential on modern TV screen technologies . This paper presents a true motion vector verification algorithm based on multi temporal block matching strategy , applied to video de-interlacing . During field scanning , a block of pixels is selected , then a block with the same reference coordinates is extracted but in the future field .
Despite these algorithms are developed using software implementations , their implementations in hardware are required to achieve real-time operation . This paper describes the development of an embedded system for video de-interlacing . The algorithm for video de-interlacing uses three fuzzy logic-based systems to tackle three relevant features in video sequences : motion , edges , and picture repetition .
Ethernet passive optical networks ( EPONs ) are designed to deliver services for numerous applications such as voice over Internet protocol , standard and high-definition video , video conferencing ( interactive video ) , and data traffic . Various dynamic bandwidth allocation and intra-optical network unit ( ONU ) scheduling algorithms have been proposed to enable EPONs to deliver differentiated services for traffic with different quality of service ( QoS ) requirements .
A mobile terminal equipped with multiple interfaces can achieve a much higher bandwidth by aggregating the bandwidth offered by the individual networks . This helps support demanding applications like interactive video . Often , in spite of bandwidth aggregation , the available bandwidth may be too small to avoid frame loss altogether .
This invention relates to a video interfacing arrangement and MPEG media type for connecting at least one display device , for example a screen-like device of television , at least one video source , consisting essentially of First , a processing unit adapted to display any type of MPEG video streams in real time or delayed , store , save and / or sent over a broadcast network ( 4 ) and / or over a wide area telecommunication network ( 10 ) and , secondly , at least one screen interface ( 7 ) and a connection interface to a local or wide area network ( 5 , 9 ) , characterized in that it comprises essentially one hand , a memory of certain B and P pictures in each audiovisual portal ( 12 ) and secondly , that each arrangement of video interfacing ( 8) has storage , recording and processing audiovisual program and is associated with at least one device screen type display television ( 6 ) , each arrangement of video interfacing ( 8) reconstructing the MPEG stream from the information of its own hard drive and algorithms and B and P pictures from the portal ( 12 ) .
In this thesis we address each of the three issues and make some original contributions . These include a new method of analyzing multidimensional filter banks ; a general technique of transforming filter banks from one dimension to another ; a complete structure for one-dimensional perfect reconstruction filter banks , which can also be used to synthesize multidimensional filter banks as well as multidimensional linear phase filter banks ; an analysis of interlaced video and applying some of the above concepts in coding of interlaced video , in particular in a multiresolution or scalable manner .
The algorithm also works well for scene change condition . Test results for coding interlaced video ( 720 x576 PAL ) are reported .
Interlaced video acquisition and transmission , used as a simple way of increasing motion quality in video sequences , all by respecting the bandwidth constraints of progressive format representation , has been extensively used by analogue transmission systems . However , considering that nowadays the television sets and the flat screens can display only progressive format input , ensuring a smooth and high quality interlaced to progressive format conversion represents a challenging task .
Hence , the structure that gives the easiest implementation can be chosen . The spatial domain structure is preferred for motion compensation and for line interlaced video signals . Interframe hybrid coding experiments are performed on interlaced videophone scenes using an adaptive transform coder .
Based on Finite Automata and Conceptual Graphs , this formalism allows to express spatial and temporal constraints , as to define sequences of events in a video and positions of objects in an image . In addition to the description of complex concepts , this formalism allows to monitor behaviors in a video-surveillance context , to detect important highlights in a sport context and also to validate MPEG7-based descriptions .
The high-performance video coding is activated as a research project of the ISO/IEC Moving Picture Experts Group in the year 2008 , and a new standardization is already under discussion and preparation . This paper gives a brief introduction to the development of this project and an overview of the related concepts and technologies .
The key to high-performance video coding lies in an efficient reduction of the temporal redundancies . For this purpose , motion estimation and compensation techniques have been successfully applied .
Besides , approaches to en- code the statistics of sequential binary data in the manifold of statistical models are proposed , resulting in the bag-of-words for attribute dynamics ( BoWAD ) and vector of locally aggregated descriptor for attribute dynamics (VLADAD).Empirical study on challenging tasks of complex human activity analysis justifies the effectiveness of the proposed framework . Our solution not only produces the state-of-the-art results for event detection , but also enables recount- ing that provides the visual evidence anchored over time in the video for the prediction , and facilitates tasks like semantic video segmentation , content based video summarization , and so forth .
A kD-tree-based nearest-neighbour search strategy is employed to accelerate the search procedure . Experimental results show that our method is computationally efficient and practically effective to build a content-based video summarization system .
Query-by-example video retrieval is receiving an increasing attention in recent years . One of the state-of-art approaches is the Bag-of-visual Words ( BoW ) based technique , where images are described by a set of local features mapped to a discrete set of visual words .
The " Bag of Visual Words " ( BoW ) framework has been widely used in query-by-example video retrieval to model the visual content by a set of quantized local feature descriptors . In this paper , we propose a novel technique to enhance BoW by the selection of Word-of-Interest ( WoI ) that utilizes the quantified temporal motion coherence of the visual words between the adjacent frames in the query example .
Keywords : Media Video Learning , Report Writting , Model Development .
Multicast addressing was chosen over the broadcast address and unicast address mechanisms for the transmission of video data over the LAN . Dynamic allocation of multicast addresses enables such features as the continuous playback of full motion video over a network with multiple viewers . Design of this video data transmission system permits interested nodes on a LAN to dynamically allocate a single multicast address from a pool of multicast addresses .
In this paper , we consider the challenging problem of object duplicate detection and localization . Several applications require efficient object duplicate detection methods , such as automatic video and image tagging , video surveillance , and high level image or video search . In this paper , a novel graph-based approach for 3D object duplicate detection in still images is proposed .
To provide a further “ taste ” of multimedia , we show how simple animations may proceed . To round out the discussion of such tasks , we consider a “ build your own ” video-transition problem , where the intent would be to generate one ’s own video transition . We then go on to review the current and future state of multimedia sharing and distribution , outlining later discussions of social media , video sharing , and new forms of TV .
Methods and systems for identifying video clips in a video clip repository that are of the same event are disclosed . Video clips are identified as being of the same event based on timestamps and geolocation stamps associated with the video clips .
However , limited by the scale of available surveillance video datasets , few existing human analysis approaches report their performances on such complex events . To this end , we present a new large-scale dataset , named Human-in-Events or HiEve ( human-centric video analysis in complex events ) , for understanding human motions , poses , and actions in a variety of realistic events , especially crowd & complex events . It contains a record number of poses ( > 1 M ) , the largest number of action labels ( > 56k ) for complex events , and one of the largest number of trajectories lasting for long terms ( with average trajectory length > 480 ) .
Visual Question Answering ( VQA ) is an emerging interdisciplinary research problem at the intersection of computer vision , natural language processing and artificial intelligence . It has many real - life applications , such as automatic querying of surveillance video or assisting the visually impaired . Compared to the recently popular image captioning task , VQA requires a deeper understanding of the image , but is considerably easier to evaluate .
Video object segmentation in the cellular neural networks architecture A modified hierarchical graph cut based video segmentation approach for high frame rate video Extraction of Video Objects via Surface Optimization and Voronoi Order Leveraging Occlusions for Causal Video Object Segmentation Object segmentation in video via graph cut built on superpixels Graphical models for object segmentation Advanced statistical and adaptive threshold techniques for moving object detection and segmentation Multimetric evaluation protocol for user-assisted video object extraction systems Probabilistic Spatio-Temporal Video Object Segmentation Incorporating Shape Information Multi-screen video preprocessing and synchronous broadcasting method and system Synchronization of Independently Moving Cameras via Motion Recovery Trajectory Based Video Sequence Synchronization Multiple-view polarimetric camera. A Macintosh-Based Scientific Images Video Analysis System Molecular modeling on the Commodore Amiga. Slice matching for accurate spatio-temporal alignment 3D-Computer Animation for a Yoruba Native Folktale Synchronization playing method based on video data block distribution Video synchronization method based on camera photographing True-Motion Estimation and Compensation with Multitemporal Block-Matching Search Fuzzy logic-based embedded system for video de-interlacing Per-Stream QoS and Admission Control in Ethernet Passive Optical Networks (EPONs) Selective frame discard for interactive video An apparatus for secure transmission, recording and viewing television programs Theory, design and structures for multidimensional biorthogonal filter banks and applications in coding of interlaced video Complexity control of fast motion estimation in H.264/MPEG-4 AVC with rate-distortion-complexity optimization Motion-compensated TV-reconstruction-based video deinterlacing Fixed and Adaptive Predictors for Hybrid Predictive/Transform Coding A Representation Language for Multimedia Semantic Web Advanced technologies for high-performance video coding A new class of feature-orientated motion estimation for motion pictures Visual Understanding of Complex Human Behavior via Attribute Dynamics Gaussian mixture vector quantization-based video summarization using independent component analysis Video Retrieval Based on Words-of-Interest Selection Words-of-interest selection based on temporal motion coherence for video retrieval Pengembangan Media Video untuk Pembelajaran Menulis Laporan Berbasis Karakter LAN Addressing for Digital Video Data Graph-based approach for 3D object duplicate detection A Taste of Multimedia MOB source phone video collaboration Human in Events: A Large-Scale Benchmark for Human-centric Video Analysis in Complex Events Ask, Attend and Answer: Exploring Question-Guided Spatial Attention for Visual Question Answering
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