Computer Vision & Pattern Recognition

Computer vision (image understanding) is a discipline that studies how to reconstruct, interpret and understand a 3D scene from its 2D images in terms of the properties of the structures present in the scene. The ultimate goal of computer vision is to model, replicate, and more importantly exceed human vision using computer software and hardware at different levels.

Pattern Recognition techniques related to real-world problems, interdisciplinary research, experimental and/or theoretical studies yielding new insights that advance Pattern Recognition methods are especially encouraged.

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  • Object Recognition
  • Motion/Stereo Processing and Augmented Reality
  • Face Detection and Recognition
  • Gesture/Hand Recognition
  • Human Motion Analysis/Capture
  • Action Recognition
  • Human-Computer Interaction
  • Computational Photography
  • Vision for Robotics
  • Vision for Graphics
  • Vision for Web
  • Real-time Tracking
  • Optimization methods
  • Physics-based vision and shape-from-X
  • Recognition: detection, categorization, indexing, matching
  • Segmentation, grouping and shape representation
  • Video: events, activities and surveillance
  • Applications and research

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