By Edited by Andreas Koschan, Marc Pollefeys, Mongi Abidi
This ebook provides the completely revised types of lectures given through major researchers throughout the Workshop on complex 3D Imaging for security and safety along with the overseas convention on machine imaginative and prescient and development acceptance CVPR 2005, held in San Diego, CA, united states in June 2005. It covers the present cutting-edge in 3D imaging for security and safety.
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Additional info for 3D Imaging for Safety and Security (Computational Imaging and Vision)
Wrl, supports 54 different types of nodes - some of them for interactive visualization. To save space, oftentimes surface with less detail is represented with fewer numbers of polygons or control parameters. Smooth surfaces use fewer control parameters than surfaces with more details. Along with local shape, these parameters may have control over the global shape34. com) supports lines, polygons described in terms of their points and free-form curves and surfaces defined with control points. MDL, developed by Cornell University, is fast to read (hence visualize) and write and is reasonably space-efficient.
This method requires registration of the 3D model with 2D images. It is not necessary to register the whole 3D model since not all the regions of human faces are difficult to match. Baker et al. have used prior knowledge of only the nose for its better reconstruction46. In the second category, structured light is projected on the face while capturing the stereo images. The structured light images are then matched almost explicitly. 47 and D’Apuzzo48 where the authors exploited noise like patterns for matching.
Bowyer, and P. J. Flynn. An Evaluation of Multimodal 2D+3D Face Biometrics. IEEE Trans. Pattern Anal. Mach. , 27(4):619-624, 2005. 8. C. Chua, F. Han, and Y. Ho. 3D human face recognition using point signature. In Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 233-238, 2000. 9. C. Chua and R. Jarvis. Point Signatures: A New Representation for 3D Object Recognition. Int. J. Comput. Vision, 25(1):63-85, 1997. 3D Assisted Face Recognition: A Survey 21 10.
3D Imaging for Safety and Security (Computational Imaging and Vision) by Edited by Andreas Koschan, Marc Pollefeys, Mongi Abidi