Object Tracking With Structured Metric Learning

Structured Learning for Multiple Object Tracking

Many adaptive tracking-by-detection methods have been proposed to track object with slowly changing appearance. However, most of those methods are designed for single object tracking. This paper proposes a method for adaptively tracking multiple objects based on a modified structured Support Vector Machine (SVM). The method utilizes the inter-object constraints and the layout information, which...

Learning structured visual dictionary for object tracking

Object Tracking Using On-line Distance Metric Learning

In order to improve the real-time quality and precision of object tracking, an algrithm using distance metric learning is studied. First, instances are selected around the objects, and features vectors are extracted by using the compress sensing theory. Second, distance metric is trained according to the random projection theory. Finally, the Mahalanobis distance of target object and possible i...

Incremental Structured Dictionary Learning for Video Sensor-Based Object Tracking

To tackle robust object tracking for video sensor-based applications, an online discriminative algorithm based on incremental discriminative structured dictionary learning (IDSDL-VT) is presented. In our framework, a discriminative dictionary combining both positive, negative and trivial patches is designed to sparsely represent the overlapped target patches. Then, a local update (LU) strategy ...

Robust Tracking with Weighted Online Structured Learning

Robust visual tracking requires constant update of the target appearance model, but without losing track of previous appearance information. One of the difficulties with the online learning approach to this problem has been a lack of flexibility in the modelling of the inevitable variations in target and scene appearance over time. The traditional online learning approach to the problem treats ...