Object tracking is one of the most important components in numerous applications of
computer vision. While much progress has been made in recent years with efforts on sharing …

Visual tracking using multiple features has been proved as a robust approach because
features could complement each other. Since different types of variations such as …

Combining multiple observation views has proven beneficial for tracking. In this paper, we
cast tracking as a novel multi-task multi-view sparse learning problem and exploit the cues …

Cross-correlator plays a significant role in many visual perception tasks, such as object
detection and tracking. Beyond the linear cross-correlator, this paper proposes a kernel …

Random forest has emerged as a powerful classification technique with promising results in
various vision tasks including image classification, pose estimation and object detection …

Sparse representation has been recently extensively studied for visual tracking and
generally facilitates more accurate tracking results than classic methods. In this paper, we …

Information fusion utilizes a collection of data sources for uncertainty reduction, coverage
extension, and situation awareness. Future information fusion solutions require systems …

Object tracking toward satellite videos faces various challenges, such as small size of the
moving object, few texture, background similarities, etc. In this article, we propose a high …

In long-term object tracking, severe occlusion and deformation could happen to the targets.
Due to the accumulation and propagation of estimation errors, even a few frames of full …

In visual tracking, holistic and part-based representations are both popular choices to model
target appearance. The former is known for great efficiency and convenience, while the latter …