BibTeX:

@article{IJIRSTV4I3017,
     title={Object Detection and Tracking from Video Sequence using MATLAB},
     author={S. Saranya},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={4},
     number={3},
     pages={43--47},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV4I3017.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

This paper aims to detecting and tracking objects in a sequence of color images taken from a video camera. Motion detection and tracking algorithm is presented for monitoring the pedestrians in an outdoor scene from a fixed camera. A mixture of Gaussians is used to model each pixel of the background image and thus adaptive to the dynamic scene. Color chromaticity is used as the image representation, which results in the illumination-invariant change detection in a day lit environment. To correctly interpret those objects that are occluded, merged, split or exit from the scene, a scene model is created and the motion of each object is predicted. A Bayesian network is constructed to reason about the uncertainty in the tracking. The results for detecting and tracking the moving objects in the PETS sequences are demonstrated.

Matlab, Object detection, Network, Robust