The Experts below are selected from a list of 52062 Experts worldwide ranked by ideXlab platform

Dimitrios Makris - One of the best experts on this subject based on the ideXlab platform.

  • Hierarchical database for a multi-Camera surveillance system
    Pattern Analysis and Applications, 2004
    Co-Authors: J Black, Dimitrios Makris, Tim Ellis
    Abstract:

    This paper presents a framework for event detection and video content analysis for visual surveillance applications. The system is able to coordinate the tracking of objects between Multiple Camera views, which may be overlapping or non-overlapping. The key novelty of our approach is that we can automatically learn a semantic scene model for a surveillance region, and have defined data models to support the storage of tracking data with different layers of abstraction into a surveillance database. The surveillance database provides a mechanism to generate video content summaries of objects detected by the system across the entire surveillance region in terms of the semantic scene model. In addition, the surveillance database supports spatio-temporal queries, which can be applied for event detection and notification applications.

  • a hierarchical database for visual surveillance applications
    International Conference on Multimedia and Expo, 2004
    Co-Authors: J Black, Tim Ellis, Dimitrios Makris
    Abstract:

    This paper presents a framework for event detection and video content analysis for visual surveillance applications. The system is able to coordinate the tracking of objects between Multiple Camera views, which may be overlapping or non-overlapping. The key novelty of our approach is that we can automatically learn a semantic scene model for a surveillance region, and have defined data models to support the storage of different layers of abstraction of tracking data into a surveillance database. The surveillance database provides a mechanism to generate video content summaries of objects detected by the system across the entire surveillance region in terms of the semantic scene model. In addition, the surveillance database supports spatio-temporal queries, which can be applied for event detection and notification applications

  • ICME - A hierarchical database for visual surveillance applications
    2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763), 2004
    Co-Authors: J Black, Tim Ellis, Dimitrios Makris
    Abstract:

    This paper presents a framework for event detection and video content analysis for visual surveillance applications. The system is able to coordinate the tracking of objects between Multiple Camera views, which may be overlapping or non-overlapping. The key novelty of our approach is that we can automatically learn a semantic scene model for a surveillance region, and have defined data models to support the storage of different layers of abstraction of tracking data into a surveillance database. The surveillance database provides a mechanism to generate video content summaries of objects detected by the system across the entire surveillance region in terms of the semantic scene model. In addition, the surveillance database supports spatio-temporal queries, which can be applied for event detection and notification applications

Takashi Matsuyama - One of the best experts on this subject based on the ideXlab platform.

  • The Multiple-Camera 3-D production studio
    IEEE Transactions on Circuits and Systems for Video Technology, 2009
    Co-Authors: Jonathan Starek, Allan Hilton, Atsuto Maki, Shohei Nobuhara, Takashi Matsuyama
    Abstract:

    Multiple-Camera systems are currently widely used in research and development as a means of capturing and synthesizing realistic 3-D video content. Studio systems for 3-D production of human performance are reviewed from the literature, and the practical experience gained in developing prototype studios is reported across two research laboratories. System design should consider the studio backdrop for foreground matting, lighting for ambient illumination, Camera acquisition hardware, the Camera configuration for scene capture, and accurate geometric and photometric Camera calibration. A ground-truth evaluation is performed to quantify the effect of different constraints on the Multiple-Camera system in terms of geometric accuracy and the requirement for high-quality view synthesis. As changing Camera height has only a limited influence on surface visibility, Multiple-Camera sets or an active vision system may be required for wide area capture, and accurate reconstruction requires a Camera baseline of 25deg, and the achievable accuracy is 5-10-mm at current Camera resolutions. Accuracy is inherently limited, and view-dependent rendering is required for view synthesis with sub-pixel accuracy where display resolutions match Camera resolutions. The two prototype studios are contrasted and state-of-the-art techniques for 3-D content production demonstrated.

Radu Horaud - One of the best experts on this subject based on the ideXlab platform.

  • Multiple Camera Calibration using Robust Perspective Factorization
    2006
    Co-Authors: Andrei Zaharescu, Radu Horaud, Rémi Ronfard, Loic Lefort
    Abstract:

    In this paper we address the problem of recovering structure and motion from a large number of intrinsically calibrated perspective Cameras. We describe a method that combines (1) weak-perspective reconstruction in the presence of noisy and missing data and (2) an algorithm that updates weakperspective reconstruction to perspective reconstruction by incrementally estimating the projective depths. The method also solves for the reversal ambiguity associated with affine factorization techniques. The method has been successfully applied to the problem of calibrating the external parameters (position and orientation) of several Multiple-Camera setups. Results obtained with synthetic and experimental data compare favourably with results obtained with nonlinear minimization such as bundle adjustment.

  • Multiple-Camera tracking of rigid objects
    International Journal of Robotics Research, 2002
    Co-Authors: Frédérick Martin, Radu Horaud
    Abstract:

    In this paper we describe a method for tracking rigid objects using\none or several Cameras. The tracking process consists of aligning\na 3-D model representation of an object with image contours by measuring\nand minimizing the image error between predicted model points and\nimage contours. The tracker behaves like a visual servo loop where\nthe internal and external Camera parameters are updated at each new\nimage acquisition. We study in detail the Jacobian matrix associated\nwith this minimization process in the presence of both point-to-point\nand point-to-contour matches. We establish the minimal number of\nmatches that are needed as well as the singular configurations leading\nto a rank-deficient Jacobian matrix. We find a mathematical link\nbetween the point-to-point and point-to-contour cases. Based on this\nlink we show that the latter has the same kind of singularities as\nthe former. Moreover, we study Multiple-Camera configurations which\noptimize the robustness of the method in the presence of single-Camera\nsingularities, bad, noisy, or missing data. Extensive experiments\ndone with a complex ship part and with up to three Cameras validate\nthe method. In particular we show that the tracker may well be used\nas a Camera calibration procedure.

J Black - One of the best experts on this subject based on the ideXlab platform.

  • Hierarchical database for a multi-Camera surveillance system
    Pattern Analysis and Applications, 2004
    Co-Authors: J Black, Dimitrios Makris, Tim Ellis
    Abstract:

    This paper presents a framework for event detection and video content analysis for visual surveillance applications. The system is able to coordinate the tracking of objects between Multiple Camera views, which may be overlapping or non-overlapping. The key novelty of our approach is that we can automatically learn a semantic scene model for a surveillance region, and have defined data models to support the storage of tracking data with different layers of abstraction into a surveillance database. The surveillance database provides a mechanism to generate video content summaries of objects detected by the system across the entire surveillance region in terms of the semantic scene model. In addition, the surveillance database supports spatio-temporal queries, which can be applied for event detection and notification applications.

  • a hierarchical database for visual surveillance applications
    International Conference on Multimedia and Expo, 2004
    Co-Authors: J Black, Tim Ellis, Dimitrios Makris
    Abstract:

    This paper presents a framework for event detection and video content analysis for visual surveillance applications. The system is able to coordinate the tracking of objects between Multiple Camera views, which may be overlapping or non-overlapping. The key novelty of our approach is that we can automatically learn a semantic scene model for a surveillance region, and have defined data models to support the storage of different layers of abstraction of tracking data into a surveillance database. The surveillance database provides a mechanism to generate video content summaries of objects detected by the system across the entire surveillance region in terms of the semantic scene model. In addition, the surveillance database supports spatio-temporal queries, which can be applied for event detection and notification applications

  • ICME - A hierarchical database for visual surveillance applications
    2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763), 2004
    Co-Authors: J Black, Tim Ellis, Dimitrios Makris
    Abstract:

    This paper presents a framework for event detection and video content analysis for visual surveillance applications. The system is able to coordinate the tracking of objects between Multiple Camera views, which may be overlapping or non-overlapping. The key novelty of our approach is that we can automatically learn a semantic scene model for a surveillance region, and have defined data models to support the storage of different layers of abstraction of tracking data into a surveillance database. The surveillance database provides a mechanism to generate video content summaries of objects detected by the system across the entire surveillance region in terms of the semantic scene model. In addition, the surveillance database supports spatio-temporal queries, which can be applied for event detection and notification applications

Jan Peters - One of the best experts on this subject based on the ideXlab platform.