This paper presents a novel tracking algorithm which integrates two complementary
trackers. Firstly, an improved Bayesian tracker (B-tracker) with adaptive learning rate is …

Visual tracking is challenging due to image variations caused by various factors, such as
object deformation, scale change, illumination change, and occlusion. Given the superior …

Object tracking has always been an interesting and essential research topic in the domain of
computer vision, of which the model update mechanism is an essential work, therefore the …

In this paper, a chaotic multiple instance learning tracker based on chaos theory for a robust
and efficient online tracking is introduced. In this method, chaotic characteristics can be …

As a fundamental mathematical problem in the field of machine learning, the linear
separability test still lacks a theoretically complete and computationally efficient method. This …

It has been extensively observed that an accurate appearance model is critical to achieving
satisfactory performance for robust object tracking. Most existing top-ranked methods rely on …

为更好地应对跟踪过程中复杂的场景变化问题, 提出一种采用多种特征融合进行跟踪的方法.
算法在粒子滤波的框架下, 通过在跟踪过程中对每一个特征进行不确定性度量 …

As a development of sparse coding, while retaining the advantage of sparse coding in
classification, Locality-constrained Linear Coding (LLC) greatly improves the time efficiency …

Visual object tracking using deep features has achieved great success, particularly when
object appearances change in the presence of illumination variation, occlusion, in-plane …

In order to deal with complex scene change problem in the tracking process, we propose a
tracking algorithm via multiple feature fusion. Under the framework of particle filter, dynamic …