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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 417))

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Abstract

In the recent years, it is noticed that most road accidents are caused due to the negligence and ignorance of humans. Tracking can be used to predict the motion and/or position of objects. Tracking can help locate specific motion or specific objects. Trackers like MIL, Boosting and KCF, have been implemented and analyzed to come up with the most efficient tracking technique. Re-Identification is very useful when a particular object(s) are to be tracked and each of them are given a unique tracking identification number. This can be done with various features like texture and color. DeepSORT and YOLO can track the multiple pedestrians in a given frame. These trackers can track pedestrians at various speeds and of various sizes. Re-Identification of a pedestrian is done by identifying pedestrians uniquely with an individual identification number that is done by using different texture and color parameters of an image. If a given pedestrian goes out the frame of the video and comes back into the frame later, he/she is identified with the same identification number and also tracked successfully.

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Correspondence to P. C. Nissimagoudar .

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Nissimagoudar, P.C., Iyer, N.C., Gireesha, H.M., Pillai, P., Mallapur, S. (2022). Multi-pedestrian Tracking and Person Re-identification. In: Abraham, A., et al. Proceedings of the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021). SoCPaR 2021. Lecture Notes in Networks and Systems, vol 417. Springer, Cham. https://doi.org/10.1007/978-3-030-96302-6_16

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