Towards model-based recognition of human movements in image sequences
CVGIP: Image Understanding
Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
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This paper presents a method to detect and track multiple pedestrians from a moving camera. First, a BMA(Block Matching Algorithm) is used to obtain a motion vector from two consecutive input frames. A frame difference image is then generated by the motion compensation with the motion vector. Second, pedestrians are detected by the step that the frame difference image is transformed into binary image, a noise is deleted and a projection histogram is processed. And a color histogram is applied on the obtained pedestrian region to separate from adjacent pedestrians. Finally, color segmentation and color mean value is used to track the detected pedestrians. The experimental results on our test sequences demonstrated the high efficiency of our method.