Abstract
AbstractCollaborative object detection by multiple cameras can make up for the limitation of insufficient field of view of a single camera, and through the rich information obtained from multiple perspectives, object detection and other tasks can be better completed. For the sake of detect moving object in multiple cameras in real time and accurately, a moving object detection algorithm based on improved ORB feature matching was proposed. In the first place, the ORB algorithm was used to extract and describe the feature points. Then, in order to improve the accuracy of feature matching, BF and grid-based motion statistics were combined to eliminate the wrong matching pairs. Finally, through time synchronization of multiple cameras, the matching results of each camera were selected to obtain the final detection results. Experimental results show that this algorithm apart from maintains the superiority of ORB itself, it also improves the detection accuracy of the improved feature matching algorithm, which can accurately detect the moving object between multiple cameras in real time.KeywordsMoving object detectionORB feature matchingMulti-camera collaboration
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