title: What is the best suited method for detecting images using android device for markerless detection?
body: <p>I'm trying to create an android application for detecting objects from camera using openCV, I read the openCV reference and found there are many methods for image detection,</p>
  
  <p>my purpose is to create an application </p>
  
  <p>1) App can detect the any object from database(set of objects that can be detected) on real time camera frame.(Speed of processing/detection is important)</p>
  
  <p>2) The database of object images will be updated from time to time.(database preferably on an external server) - Does this mean I cannot use cascade classifier, HOG or any machine learing methods?</p>
  
  <p>3) The camera frame may sometimes have two or more objects that are in database can both be detected in this case?</p>
  
  <p>I tried a simple feature detection with ORB detection and description and bruteforce matching but gives detection for almost any object or even a wall - false positive detection.(using SIFT or SURF for testing even throws error)</p>
  
  <pre><code>FeatureDetector detector = FeatureDetector.create(FeatureDetector.ORB);
  DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.ORB);
  DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE);
  </code></pre>
  
  <p>I dont need any homography or perspective since I'm not going to project anything just a robust method to detect presence of object.</p>