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Computer vision is the science and technology of making machines that see. It is concerned with the theory, design and implementation of algorithms that can automatically process visual data to recognize objects, track and recover their shape and spatial layout. This type of processing typically needs input data provided by a computer vision system, acting as a vision sensor and providing high-level information about the environment and the robot. Other parts which sometimes are described as belonging to artificial intelligence and which are used in relation to computer vision is pattern recognition and learning techniques. Researchers are hereby invited to submit a full paper (5–6 pages) detailing their research, or a short paper (max 4 pages) describing their work-in-progress. All submitted papers will be subject to peer reviewing by at least two reviewers for technical merit, significance and relevance to the topics. Submission implies the willingness of at least one author per paper to register, attend the conference and present the paper. Proceedings will be published on IEEE Xplore.

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Topics of interest include all aspects of computer vision and image analysis including, but not limited to:

  • Computer Vision Theory

  • 3D Computer Vision

  • Action Recognition

  • Biometrics

  • Big Data, Large Scale Methods

  • Deep Learning

  • Face and Gesture

  • Image Processing

  • Medical, Biological and Cell Microsopy Image Analysis

  • Motion and Tracking

  • Performance Evaluation and Benchmark Data Sets

  • Recognition: Detection, Categorization, Indexing Segmentation, Grouping and Shape Representation

  • Vision for Web Applications

  • Video analysis

  • Vision for quality assurance, medical diagnosis, etc

  • Features Extraction

  • Visual Attention and Image Saliency

  • Machine Learning Technologies for Vision · Object and Face Recognition

  • Object detection and Localization

  • Categorization and Scene Understanding

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重要日期
  • 会议日期

    09月27日

    2017

    09月29日

    2017

  • 09月29日 2017

    注册截止日期

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