Visual object tracking performance measures revisited

Video object tracking with feedback of performance measures

We present a scalable object tracking framework, which is capable of tracking the contour of nonrigid objects in the presence of occlusion. The framework consists of open-loop boundary prediction and closed-loop boundary correction parts. The open-loop prediction block adaptively divides the object contour into subcontours, and estimates the mapping parameters for each subsegment. The closed-lo...

Video Object Tracking with Feedback of Performance Measures

The Effect of Visual Distinctiveness on Multiple Object Tracking Performance

Observers often need to attentively track moving objects. In everyday life, such objects are often visually distinctive. Previous studies have shown that tracking accuracy is increased when the targets contain a visual feature (e.g., a color) not possessed by the distractors. Conversely, a gain in tracking accuracy was not observed when the targets differed from the distractors by only a conjun...

Convolutional Gating Network for Object Tracking

Object tracking through multiple cameras is a popular research topic in security and surveillance systems especially when human objects are the target. However, occlusion is one of the challenging problems for the tracking process. This paper proposes a multiple-camera-based cooperative tracking method to overcome the occlusion problem.  The paper presents a new model for combining convolutiona...

Integrated Object Models for Robust Visual Tracking

The robustness of visual tracking, or following the movement of objects in images, can be improved with an explicit model for the objects being tracked. In this paper, we investigate the use of an object model in this way. An object geometric model can tell us what feature movements to expect, and what those movements reveal about object motion. We characterize the tracking problem as one of pa...