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| T. Shakunaga, "3-D Corridor Modeling from a Single View Under Natural Lighting Conditions," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 2, pp. 293-298, February, 1992. | |||
| BibTex | x | ||
| @article{ 10.1109/34.121796, author = {T. Shakunaga}, title = {3-D Corridor Modeling from a Single View Under Natural Lighting Conditions}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {14}, number = {2}, issn = {0162-8828}, year = {1992}, pages = {293-298}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.121796}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Pattern Analysis and Machine Intelligence TI - 3-D Corridor Modeling from a Single View Under Natural Lighting Conditions IS - 2 SN - 0162-8828 SP293 EP298 EPD - 293-298 A1 - T. Shakunaga, PY - 1992 KW - 3D indoor scene modelling; 3D corridor scene; pattern recognition; computer vision; single view analysis; generic object model; camera; rectangular parallelepiped; bottom-up image processing; model-based interpretation; computer vision; pattern recognition; picture processing VL - 14 JA - IEEE Transactions on Pattern Analysis and Machine Intelligence ER - | |||
The author discusses the modeling of a 3-D indoor scene from a single view using a generic object model. It is assumed that an image is made by a well-calibrated camera, and that the camera height above the floor is known. The image is assumed to be a projection of a natural corridor scene from which a generic model is known, but the specific model is unknown. This system can model any corridor that satisfies the following conditions: (1) the corridor is a rectangular parallelepiped, (2) there are several lines along each axis of the rectangle parallelepiped, (3) there are not many parallel lines in directions other than along the principal axes, and (4) corridor height is within a known range. The system for 3-D modeling from a single view of such a corridor consists of a robust bottom-up image processing part and a top-down, model-based interpretation part. Experimental results show that specific corridor models can be recovered from a single view with an approximately 1% estimation error.
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