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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Face Detection and Gesture Recognition for Human-Computer Interaction

Face Detection and Gesture Recognition for Human-Computer Interaction

Ming-Hsuan Yang
Ahuja, Narendra

Paperback

Series: The International Video Computing, Book 1

Technology & Engineering

ISBN10: 146135546X
ISBN13: 9781461355465
Publisher: Springer Nature
Published: Nov 9 2012
Pages: 182
Weight: 0.63
Height: 0.42 Width: 6.14 Depth: 9.21
Language: English
Traditionally, scientific fields have defined boundaries, and scientists work on research problems within those boundaries. However, from time to time those boundaries get shifted or blurred to evolve new fields. For instance, the original goal of computer vision was to understand a single image of a scene, by identifying objects, their structure, and spatial arrangements. This has been referred to as image understanding. Recently, computer vision has gradually been making the transition away from understanding single images to analyzing image sequences, or video understanding. Video understanding deals with understanding of video sequences, e. g., recognition of gestures, activities, facial expressions, etc. The main shift in the classic paradigm has been from the recognition of static objects in the scene to motion-based recognition of actions and events. Video understanding has overlapping research problems with other fields, therefore blurring the fixed boundaries. Computer graphics, image processing, and video databases have obvious overlap with computer vision. The main goal of computer graphics is to gener- ate and animate realistic looking images, and videos. Researchers in computer graphics are increasingly employing techniques from computer vision to gen- erate the synthetic imagery. A good example of this is image-based rendering and modeling techniques, in which geometry, appearance, and lighting is de- rived from real images using computer vision techniques. Here the shift is from synthesis to analysis followed by synthesis.

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