Integrating object segmentation for robust object tracking

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Video object tracking is an active research field with applications diverse as augmented reality, self-navigation systems (drones or self-driving cars), human-computer interactions, hyper-linked social video, or athlete performance monitoring. Tracking is performed on raw video signals, captured typically from a single camera; different types of objects can be tracked, such as persons, athletes, vehicles, animals, or ships. Tracking of objects across real-world video signals has many challenges such as variations in object appearance due to scale change, occlusion, articulation, deformation, and interactions of multiple objects.