| Presentation | 2002/11/15 A Trainable Object-Tracking Method using Equivalent Retinotopical Sampling Hirotaka NIITSUMA, |
|---|---|
| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this article, a maximum likelihood based trainable object tracking method is proposed. The concept of Retinotopical Sampling (RS) was inspired by human saccadic eye movements and enables a quick recognition of eyes, mouth in static images. However, when the object size is inferred by RS the result tends to gravitate towards zero. In this article, Equivalent Retinotopical Sampling(ERS), which is an extension of RS, is proposed. ERS can infer the size of objects more accurately. Using ERS, a trainable object tracking method, with essentially only two parameters, has been formulated. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Retinotopical Sampling / Maximum Likelihood / Object Tracking |
| Paper # | PRMU2002-127 |
| Date of Issue |
| Conference Information | |
| Committee | PRMU |
|---|---|
| Conference Date | 2002/11/15(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | |
| Vice Chair | |
| Secretary | |
| Assistant | |
| Paper Information | |
| Registration To | Pattern Recognition and Media Understanding (PRMU) |
|---|---|
| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Trainable Object-Tracking Method using Equivalent Retinotopical Sampling |
| Sub Title (in English) | |
| Keyword(1) | Retinotopical Sampling |
| Keyword(2) | Maximum Likelihood |
| Keyword(3) | Object Tracking |
| 1st Author's Name | Hirotaka NIITSUMA |
| 1st Author's Affiliation | DENSO IT LABORATORY, INC.() |
| Date | 2002/11/15 |
| Paper # | PRMU2002-127 |
| Volume (vol) | vol.102 |
| Number (no) | 471 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |