Integrating object segmentation for robust object tracking

视频对象跟踪是一个活跃的研究领域，其应用范围广泛，如增强现实，自导航系统（无人机或自动驾驶汽车），人机交互，超链接社交视频或运动员表现监控。跟踪是在原始视频信号上执行的，通常从单个摄像机捕获;可以跟踪不同类型的对象，例如人，运动员，车辆，动物或船只。跨真实世界视频信号的对象跟踪具有许多挑战，诸如由于尺度变化、遮挡、接合、变形和多个对象的交互而导致的对象外观的变化。

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.