<p>I believe both problems that you mention (Segmentation and Detection) are still considered as open problems, therefore, there isn't a final solution. However, In the last years many works has been done to solve object detection and semantic segmentation using deeplearning with great performance and speed. </p>

<p>For Object Detection in real time I recommend to you check the results of <a href="http://pjreddie.com/darknet/yolo/" rel="nofollow noreferrer">YOLO</a> and <a href="https://arxiv.org/abs/1512.02325" rel="nofollow noreferrer">SSD</a> and take a look also of <a href="https://arxiv.org/pdf/1506.01497.pdf" rel="nofollow noreferrer">Faster R-CNN</a> since your requirements of 10Hz can be archive for it.</p>

<p>In the case of Object Segmentation you can try with <a href="https://arxiv.org/abs/1412.7062" rel="nofollow noreferrer">DCNN</a> that claims 8 fps. There are others, such as, DeepLab or FCN but I am not clear what is the speed of those systems/architectures.</p>
What is best Real Time algorithms for image segmentation and object detection (indoor environment)?
<p>I want to segment indoor area and find objects. Then, I want to use stereo vision to find Cartesian position of objects. The final goal is picking objects on a table (and controlling the trajectory) by a robot.</p>

<p>Example of object: chair, table, pen, syringe, stapler, cup, screw, toy doll, ruler, small box, milk, fruits, ....</p>

<p>My first priority is being real time (10 Hz).</p>

<p>I use ZED Stereo Camera to capture images in windows 10 64 bit, MATLAB 2016b 64 bit, on Intel core i7-3820 (3.6 GHz).</p>

<p>The camera output is color 720x2560 pixel which is combination of two (right and left image) 720x1280.</p>

<p>I prefer to use unsupervised algorithms for finding position of unknown object on table. However, it should be down in real time. If it is no possible in real time, I will degrade my expectation and will use supervised algorithms to find predefined object.</p>