What is it about?
This paper describes computer vision algorithms for detection, identification, and tracking of moving objects in a video file. The problem of multiple object tracking can be divided into two parts; detecting moving objects in each frame and associating the detections corresponding to the same object over time. New Video tracking algorithm was successfully tested using the standard walking pedestrians datasets.
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Why is it important?
The experimental results show that system can operate in real time and successfully detect, track and identify multiple targets in the presence of partial occlusion.
Perspectives
The likelihood of tracking errors can be reduced by using a more complex motion model, such as constant acceleration, by using an Extended Kalman filter or Partical filter. Also, other cues could be incorporated for associating detentions over time, such as size, shape, and colour.
Dr Milan MS Simic
RMIT University
Read the Original
This page is a summary of: Multi Object Detection and Tracking from Video File, Applied Mechanics and Materials, February 2014, Trans Tech Publications,
DOI: 10.4028/www.scientific.net/amm.533.218.
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