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We present a novel approach to non-rigid object tracking based on a supervised level set model (SLSM). In contrast with conventional level set models, which emphasize the intensity consistency only and consider no priors, the curve evolution of the proposed SLSM is object-oriented and supervised by the specific knowledge of the target we want to track.(More)
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)
Symmetric Positive Definite (SPD) matrices in the form of region covariances are considered rich descriptors for images and videos. Recent studies suggest that exploiting the Rie-mannian geometry of the SPD manifolds could lead to improved performances for vision applications. For tasks involving processing large-scale and dynamic data in computer vision,(More)
Existing works on action recognition rely on two separate stages: (1) designing hand-designed features or learning features from video data; (2) classifying features using a clas-sifier such as SVM or AdaBoost. Motivated by two observations: (1) independent component analysis (ICA) is capable of encoding intrinsic features underlying video data; and (2)(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)
Bitterness in cucumber fruit and foliage is due to the presence of cucurbitacins. Several genes have been described that control the trait, with bi (bi-1) making fruit and foliage bitter free and Bt (Bt-1) making the fruit highly bitter. Previous studies have reported the inheritance and molecular markers linked to bi-1 or Bt-1, but we were interested in(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)