Image generating method, object detecting method, object...

Image analysis – Image transformation or preprocessing – Combining image portions

Reexamination Certificate

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Reexamination Certificate

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07747104

ABSTRACT:
A small region panorama image group (I1P, I2P, I3P) is generated in advance. The small region panorama image group (I1P, I2P, I3P) includes images including a common shooting range, being composed of a plurality of common partially overlapped regions (A, B, C, D), and having independency from each other in each partially overlapped region (A, B, C, D). With the use of the small region panorama image group (I1P, I2P, I3P), a predicted background image is generated in which light source environment is the same as that of a shot target image.

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Fischler, M. A., et al, “Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography,” Communications of the Association for Computing Machinery, vol. 24, Issue 6, Jun. 1981, pp. 381-395.
Ishii, Y. et al, “Photometric Linearization Based on Classification of Photometric Factors,” (Collection of Meeting on Image Recognition and Comprehension) (MIRU 2002), vol. 2, pp. 167-176, 2002).
Okabe, T. et al, “Separation of Reflection Components Based on Frequency Characteristics of Bidirectional Reflectance Distribution Functions,” Technical Report of Information Processing Society of Japan, CVIM 2002-134-1, pp. 1-8, 2002.
Shashua, A. et al, “The Quotient Image: Class-Based Re-Rendering and Recognition with Varying Illuminations,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, No. 2, Feb. 2001, pp. 129-139.
Weng et al.,“Computer Vision Technology Review and Future Prospects,” New Technology Communication, 1998, pp. 42-44, Partial English Translation.
“Research and Development report from Natural Vision Research & Development Project (Advanced Video Display/Transmission System) 2000,” Communication and Broadcast Organization, 2001, pp. 51-53, Partial English Translation.
Shashua, A., “Geometry and Photometry in 3D Visual Recognition,” Ph. D thesis, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Nov., 1992, Cambridge, MA.
Fischler, M. A., et al, “Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography,” Communications of the Association for Computing Machinery, vol. 24, Issue 6, Jun. 1981, pp. 381-395.
Ishii, Y. et al, “Photometric Linearization Based on Classification of Photometric Factors,” (Collection of Meeting on Image Recognition and Comprehension) (MIRU 2002), vol. 2, pp. 167-176, 2002).
Okabe, T. et al, “Separation of Reflection Components Based on Frequency Characteristics of Bidirectional Reflectance Distribution Functions,” Technical Report of Information Processing Society of Japan, CVIM 2002 -134-1, pp. 1-8, 2002.
Shashua, A. et al, “The Quotient Image: Class-Based Re-Rendering and Recognition with Varying Illuminations,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, No. 2, Feb. 2001, pp. 129 -139.

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