While color information is known to provide rich discriminative clues for visual inference,
most modern visual trackers limit themselves to the grayscale realm. Despite recent efforts to …

Variations in the appearance of a tracked object, such as changes in geometry/photometry,
camera viewpoint, illumination, or partial occlusion, pose a major challenge to object …

Correlation filter based trackers are ranked top in terms of performances. Nevertheless, they
only employ a single kernel at a time. In this paper, we will derive a multi-kernel correlation …

We propose an online tracking algorithm that adaptively models target appearances based
on an online gradient boosting decision tree. Our algorithm is particularly useful for non-rigid …

Correlation filter (CF) based trackers are currently ranked top in terms of their performances.
Nevertheless, only some of them, such as KCF [henriques12&15] and MKCF [tang&Feng15} …

A simple yet effective object descriptor for visual tracking is proposed in this paper. We first
decompose the bounding box of a target object into multiple patches, which are described …

In this paper, we propose a novel effective non-rigid object tracking framework based on the
spatial-temporal consistent saliency detection. In contrast to most existing trackers that utilize …

We present a novel Joint Online Tracking and Segmentation (JOTS) algorithm which
integrates the multi-part tracking and segmentation into a unified energy optimization …

We propose a simple but effective tracking-by-segmentation algorithm using Absorbing
Markov Chain (AMC) on superpixel segmentation, where target state is estimated by a …

Many applications involve objects containing structure and rich content information, each
describing different feature aspects of the object. Graph learning and classification is a …