Depth-assisted Real-time 3D Object Detection for Augmented Reality

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We propose a novel method of real-time object detection that can recognize three-dimensional (3D) target objects, regardless of their texture and lighting condition changes. Our method computes a set of reference templates of a target object from both RGB and depth images, which describes the texture and geometry of the object, and fuses them for robust detection.
Issue Date
2011-11
Language
ENG
Citation

ICAT 2011

URI
http://hdl.handle.net/10203/171120
Appears in Collection
GCT-Conference Papers(학술회의논문)
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