MOTION DETECTION IN MOVING BACKGROUND USING ORB FEATURE MATCHING AND AFFINE TRANSFORM
R Ramya, B Sudhakara · IJITR · 2015
Visual surveillance systems have gained a lot of interest in the last few years due to its importance in military application and security. Surveillance cameras are installed in security sensitive areas such as banks, train stations, highways, and borders. In computer vision, moving object detection and tracking methods are the most important preliminary steps for higher-level video analysis applications. Moving objects in moving background are an important research area of image-video processing and computer vision. Feature matching is at the base of many computer vision problems, such as object recognition or structure from motion. ORB is used for feature detection and tracking. The objective is to track the moving objects in a moving video. Oriented Fast and Rotated Brief (ORB) which is a combination of two major techniques: Features from Accelerated Segment Test (FAST) and Binary Robust Independent Elementary Features (BRIEF).Mismatched features between two frames are rejected by the proposed method for a good accuracy of compensation. The Residues are removed using Logic AND Operation. To validate the proposed method, and to perform experiments that compare the properties of the proposed method to Scale Invariant Feature Transform (SIFT) based method and Speeded-Up Robust Features (SURF) based method, for both detecting accuracy and efficiency.