2006 Fiscal Year Final Research Report Summary
Research on eye contact recognition with active camera
| Project/Area Number |
16200014
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Perception information processing/Intelligent robotics
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| Research Institution | Wakayama University |
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Principal Investigator |
WADA Toshikazu Wakayama University, Faculty of System Engineering, professor, システム工学部, 教授 (00231035)
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| Co-Investigator(Kenkyū-buntansha) |
WU Haiyuan Wakayama University, Faculty of System Engineering, associate professor, システム工学部, 准教授 (70283695)
NAKAMURA Takayuki Wakayama University, Faculty of System Engineering, associate professor, システム工学部, 准教授 (50291969)
CHEN Qien Wakayama University, Faculty of System Engineering, associate professor, システム工学部, 准教授 (70263233)
KATO Takekazu Wakayama University, Faculty of System Engineering, instructor, システム工学部, 講師 (30362859)
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| Project Period (FY) |
2004 – 2006
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| Keywords | View direction estimation / Two circle method / PaLM-tree / K-means tracker / Distinctiveness / Active stereo tracking / K-d decision tree / Principal component tree |
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| Research Abstract |
In this research, we address "eye contact recognition problem", i.e., estimating a human gaze direction from a single image. This problem can be positioned in the field of Computer Vision, which was initiated by imitating human visual functions, because this problem can also be regarded as an imitation of a visual function that people are sensitive to those who watching them.
The possible approaches for realizing this peculiar function are classified into two types : 1) gaze recognition based on the iris contour shape and 2) gaze recognition based on the positional arrangement of pupils and other face organs. We investigated and compared both approaches. According to the first approach, we developed a gaze estimation algorithm based on ellipse fitting to the iris contours using an eye-model. Of course, each person has different eye ball diameter and distance between eye balls. These personal parameters can be estimated from short image sequence less than 5 seconds. After that, precise e
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ye direction estimation can be performed within NTSC video interval (33[ms]). On the other hand, we developed a gaze estimation algorithm according to the second approach. For this algorithm, we developed a learning algorithm for non-linear mapping named "PaLM-tree". By using this algorithm, we can estimate the viewing direction from the positional arrangement of face organs, to visual direction, it requires large training data and the accuracy of the vertical direction is less than the first one.
Also, we investigated problems of 3) active visual tracking for capturing high quality eye image of moving objective person and 4) recognition method for eye contact recognition. For the third problem, we developed a visual tracking algorithm adaptive to color change named "k-means tracker". This algorithm is robust against the color shift and shape deformation of the object. And we extend it to "reliability based k-means tracker" for further improvement of the robustness. We also developed another very fast tracking algorithm based on the distinctiveness of target colors. By using these algorithms, high performance active stereo tracking system have been constructed. For the fourth problem, we developed an accelerated algorithm of nearest neighbor classification named "k-d decision tree". Currently, this is the world fastest nearest neighbor classifier. Less
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