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Conference Paper
Dense 3D Depth Map with DOE Pattern
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- Authors
- Seung Min Choi, Jae-chan Jeong, Jiho Chang
- Issue Date
- 2012-11
- Citation
- International Conference on Ubiquitous Robots and Ambient Intelligence (URAI) 2012, pp.34-37
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- In this paper, we try to find the answer of question, 'How dense does the projected pattern have to be in order to recognize 3D fingers over 3m distance (indoor watching TV environment)'. To solve this problem, we investigate the structured light pattern projected by the laser light source and taken back through the IR camera. For 3D correspondence matching, a simple block matching algorithm from OpenCV2.4 is used. We use Canon 650D DSLR camera (removing IR-cut filter) to capture the scene, and commercial DOE product to make patterns. According to the result, at least 22.8% white dot pattern at black background is needed to recognize 3D finger shape in smart TV environment in 1296 * 864 resolution images. The experimental results could be used as such analysis or the development of new 3D sensor based structured light. Copyright © 2012 IEEE.
- KSP Keywords
- 3D depth, 3D sensors, Block Matching Algorithm, Correspondence Matching, Depth Map, Dot pattern, IR camera, Laser light source, Light pattern, Sensor based, Structured light