The Experts below are selected from a list of 21309 Experts worldwide ranked by ideXlab platform

C.-c.j. Kuo - One of the best experts on this subject based on the ideXlab platform.

  • semantic video content abstraction based on multiple cues
    International Conference on Multimedia and Expo, 2001
    Co-Authors: Wei Ming, C.-c.j. Kuo
    Abstract:

    This research addresses the problem of automatically extracting video’s semantic structure and summarizing it in a Hierarchical Manner. Multiple media cues are employed in this procedure including visual, audio and text information. The generated hierarchy can provide us a compact yet meaningful abstraction of the video data similar to the conventional table-of-contents, which will facilitate user’s access to multimedia contents including browsing and retrieval. Preliminary experiments of integrating different media for Hierarchically representing video semantics have yielded encouraging results.

  • ICME - Semantic video content abstraction based on multiple cues
    IEEE International Conference on Multimedia and Expo 2001. ICME 2001., 2001
    Co-Authors: Wei Ming, C.-c.j. Kuo
    Abstract:

    This research addresses the problem of automatically extracting video’s semantic structure and summarizing it in a Hierarchical Manner. Multiple media cues are employed in this procedure including visual, audio and text information. The generated hierarchy can provide us a compact yet meaningful abstraction of the video data similar to the conventional table-of-contents, which will facilitate user’s access to multimedia contents including browsing and retrieval. Preliminary experiments of integrating different media for Hierarchically representing video semantics have yielded encouraging results.

Wei Ming - One of the best experts on this subject based on the ideXlab platform.

  • semantic video content abstraction based on multiple cues
    International Conference on Multimedia and Expo, 2001
    Co-Authors: Wei Ming, C.-c.j. Kuo
    Abstract:

    This research addresses the problem of automatically extracting video’s semantic structure and summarizing it in a Hierarchical Manner. Multiple media cues are employed in this procedure including visual, audio and text information. The generated hierarchy can provide us a compact yet meaningful abstraction of the video data similar to the conventional table-of-contents, which will facilitate user’s access to multimedia contents including browsing and retrieval. Preliminary experiments of integrating different media for Hierarchically representing video semantics have yielded encouraging results.

  • ICME - Semantic video content abstraction based on multiple cues
    IEEE International Conference on Multimedia and Expo 2001. ICME 2001., 2001
    Co-Authors: Wei Ming, C.-c.j. Kuo
    Abstract:

    This research addresses the problem of automatically extracting video’s semantic structure and summarizing it in a Hierarchical Manner. Multiple media cues are employed in this procedure including visual, audio and text information. The generated hierarchy can provide us a compact yet meaningful abstraction of the video data similar to the conventional table-of-contents, which will facilitate user’s access to multimedia contents including browsing and retrieval. Preliminary experiments of integrating different media for Hierarchically representing video semantics have yielded encouraging results.

Tieniu Tan - One of the best experts on this subject based on the ideXlab platform.

  • Cast Shadow Removal in a Hierarchical Manner Using MRF
    IEEE Transactions on Circuits and Systems for Video Technology, 2012
    Co-Authors: Zhou Liu, Kaiqi Huang, Tieniu Tan
    Abstract:

    In this paper, we present a novel method for shadow removal using Markov random fields (MRF). In our method, we first construct the shadow model in a Hierarchical Manner. At the pixel level, we use the Gaussian mixture model to model the behavior of cast shadows for every pixel in the HSV color space. The samples which are used to update the shadow model should satisfy a pre-classifier. This pre-classifier indicates the color feature of shadow in current frame. At the global level, we exploit the statistical features of shadow in the whole scene over several consecutive frames to make this pre-classifier accurate and adaptive to the change of shadow. Then, based on the shadow model, an MRF model is constructed for shadow removal. The main contribution of this paper is twofold. First, although our method is a chroma-based method, we make the pre-classifier accurate and adaptive to the change of shadow by using the statistical features of shadow at the global level. Moreover, tracking information can make this global-level statistical information more robust. Second, we construct an MRF model to represent the dependencies between the label of a pixel and the shadow models of its neighbors. Experimental results show that the proposed method is efficient and robust.

Vlatko Bečanović - One of the best experts on this subject based on the ideXlab platform.

  • Image object classification using saccadic search, spatio-temporal pattern encoding and self-organisation
    Pattern Recognition Letters, 2000
    Co-Authors: Vlatko Bečanović
    Abstract:

    Abstract A method for extracting features from photographic images is investigated. The input image is through a saccadic search algorithm divided into a set of sub-images, segmented and coded by a spatio-temporal encoding engine. The input image is thus represented by a set of characteristic pattern signatures, well suited for classification by an unsupervised neural network. A strategy using multiple self-organising feature maps (SOM) in a Hierarchical Manner is used. With this approach, using a certain degree of user selection, a database of sub-images is grouped according to similarities in signature space.

Tatsuya Suzuki - One of the best experts on this subject based on the ideXlab platform.

  • SMC - Online signature verification system with anti-forgery provision based on segmentation and structure learning of HMM
    2010 IEEE International Conference on Systems Man and Cybernetics, 2010
    Co-Authors: Dapeng Zhang, Shinkichi Inagaki, Naoki Kanada, Tatsuya Suzuki
    Abstract:

    Inspired by forensic experts working on authentication of oriental characters like Chinese and Japanese who usually rely on distinguishing detailed features of individual strokes such as dots and straight lines, our new HMM model consisted of many sub-models each represents an individual stroke of a signature. Furthermore, 3 models were compared in 2 steps using a Hierarchical Manner. First, original user was distinguished from data corpus consisted of random forgeries; Secondly, original user was distinguished from skilled forgeries.