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This paper proposes a novel multi-layered gesture recognition method with Kinect. We explore the essential linguistic characters of gestures: the components concurrent character and the sequential organization character, in a multi-layered framework, which extracts features from both the segmented semantic units and the whole gesture sequence and then(More)
This paper proposes a scalable and credible watermarking algorithm towards Scalable Video Coding (SVC) which aims to build Copyright Protection System (CPS). Firstly, we investigate where to embed watermark to ensure it can be detected in base layer as well as enhancement layer and what does wavelet Just Noticeable Distortion (JND) for video consist of,(More)
Recently, sparse coding has been successfully applied in visual tracking. The goal of this paper is to review the state-of-the-art tracking methods based on sparse coding. We first analyze the benefits of using sparse coding in visual tracking and then categorize these methods into appearance modeling based on sparse coding (AMSC) and target searching based(More)
Traditional background modeling and subtraction methods have a strong assumption that the scenes are of static structures with limited perturbation. These methods will perform poorly in dynamic scenes. In this paper, we present a solution to this problem. We first extend the local binary patterns from spatial domain to spatio-temporal domain, and present a(More)
Handling appearance variations is a very challenging problem for visual tracking. Existing methods usually solve this problem by relying on an effective appearance model with two features: (1) being capable of discriminating the tracked target from its background, (2) being robust to the target's appearance variations during tracking. Instead of integrating(More)
Background subtraction in dynamic scenes is an important and challenging task. In this paper, we present a novel and effective method for dynamic background subtraction based on covariance matrix descriptor. The algorithm integrates two distinct levels: pixel level and region level. At the pixel level, spatial properties that are obtained from pixel(More)
In this paper, we propose a novel and robust object tracking algorithm based on sparse representation. Object tracking is formulated as a object recognition problem rather than a traditional search problem. All target candidates are considered as training samples and the target template is represented as a linear combination of all training samples. The(More)
Traditional background subtraction methods perform poorly when scenes contain dynamic backgrounds such as waving tree, spouting fountain, illumination changes, camera jitters, etc. In this paper, a novel and effective dynamic background subtraction method is presented with three contributions. First, we present a novel local dependency de-scriptor, called(More)
Intelligent video surveillance is currently one of the most active research topics in computer vision, especially when facing the explosion of video data captured by a large number of surveillance cameras. As a key step of an intelligent surveillance system, robust visual tracking is very challenging for computer vision. However, it is a basic functionality(More)
Psychophysical findings have shown that human vision system has an ability to improve target search by enhancing the representation of image components that are related to the searched target, which is the so-called feature-based visual attention. In this paper, motivated by these psychophysical findings , we propose a robust visual tracking algorithm by(More)