| Presentation | 2000/1/21 Object Recognition Based on Depth Aspect Image Matching Tomoyuki Takeguchi, Shun'ichi Kaneko, Tsukasa Kondo, Satoru Igarashi, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | A method for three dimensional object recognition based on depth image information is proposed. A depth aspect image is defiened as an orientation standardized appearance from the original depth data of the object, which is transformed by the rigid transformation drawn by each possible basis pair of every three feature points of the object depth data. They are made from the original depth images of models and then laerned in the system as the database for retrieval of any instances on the models. Matching between an object aspect and the ones from models can be performed by two-dimensional image comparison, which is based on the least quantile of residuals and is robust against occlusion possibly occurred in cluttered scene. Because this image matching procedure can be executed by some conventional hardware, the proposed recognition method has the possibility to be applied in real time systems. The paper includes a formalization of the proposed method and some experimental results with real objects. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Range data / Depth aspect image / Object recognition / Robustness / LQR / Occlusion |
| Paper # | PRMU99-214 |
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| Conference Information | |
| Committee | PRMU |
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| Conference Date | 2000/1/21(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
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| Paper Information | |
| Registration To | Pattern Recognition and Media Understanding (PRMU) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Object Recognition Based on Depth Aspect Image Matching |
| Sub Title (in English) | |
| Keyword(1) | Range data |
| Keyword(2) | Depth aspect image |
| Keyword(3) | Object recognition |
| Keyword(4) | Robustness |
| Keyword(5) | LQR |
| Keyword(6) | Occlusion |
| 1st Author's Name | Tomoyuki Takeguchi |
| 1st Author's Affiliation | Graduate School of Engineering, Hokkaido University() |
| 2nd Author's Name | Shun'ichi Kaneko |
| 2nd Author's Affiliation | Graduate School of Engineering, Hokkaido University |
| 3rd Author's Name | Tsukasa Kondo |
| 3rd Author's Affiliation | Graduate School of Engineering, Hokkaido University |
| 4th Author's Name | Satoru Igarashi |
| 4th Author's Affiliation | Graduate School of Engineering, Hokkaido University |
| Date | 2000/1/21 |
| Paper # | PRMU99-214 |
| Volume (vol) | vol.99 |
| Number (no) | 575 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |