الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
Vision-based control of Biological and Terrestrial robots needs a robust de- tection, tracking, and re-identification pipeline. In this thesis, we have chosen vehicles as viewed in surveillance camera footage to be the objects of interest for the control using an Intelligent Traffic System. Vehicle detection models were applied and compared against each other. RetinaNet has shown great performance in the detection task. About Vehicle tracking, the tracking by de- tection models specially DeepSORT proved to be more effective. In the vehicle Re-Identification task, the FastReiD pipeline was used and proved great results after training using the Veri-776 dataset. We introduce the pipeline for the Multi-camera Multi-vehicle tracking task (MCMVT) and compare the options available.