Multi Object Detection and Tracking from Video File

Abstract:

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. The detection of moving objects uses a background subtraction algorithm based on Gaussian mixture models. The motion of each track is estimated by a Kalman filter. The video tracking algorithm was successfully tested using the BIWI walking pedestrians datasets [. 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.

• Periodical: Applied Mechanics and Materials (Volume 533)
• Pages: 218-225
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.533.218
• Online since: February 2014
• Authors: Rapee Krerngkamjornkit*, Milan Simic
• Keywords: Object Detection, Object Tracking, Vision System, Visual Tracking

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