2005 Fiscal Year Final Research Report Summary
Real-time motion tracking by using spatial reticles inhomogeneously distributed according to the spatially variant distribution of receptive fields of visual peripheral nerves.
| Project/Area Number |
16500102
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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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 | The University of Electro-Communications |
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Principal Investigator |
MITSUHASHI Wataru The University of Electro-Communications, Faculty of Electro-Communications, Professor, 電気通信学部, 教授 (40017421)
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| Project Period (FY) |
2004 – 2005
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| Keywords | Real-time visual tracking / Spatial filter velocimetry / Radon transform / Kalman filter / Monocular camera / Following distance control / Motion parameter estimation |
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| Research Abstract |
A visual tracking system with real time operation for maintaining both the size and the position of the image of a moving object has been developed. In the system, a spatially variant scheme of sensor distribution is adopted for providing an effective means of analyzing global motion parameters of object motions. To achieve this, a bank of Gabor reticles was constituted in the 1st project year by mimicking the organization of the receptive field of visual peripheral nerves. The individual reticle works as a velocity sensor, and thus yielding a velocity vector field on the image plane.
Velocity sensing generally requires a wide field of view for averaging image motion, and the limited size of each reticle causes degradation in velocity estimation. The Radon transform of image motion yields a solution to this problem because of its integral feature of projection. Both translation and dilation components included in image motion can be isolated, identified and measured by evaluating the optical flow on the Radon domain.
Applying the Radon transform to the dynamic scene of a moving object enables us to visually track the object with a monocular camera system. A Kalman filter is also introduced to smoothly predict the position of the object and improve the delay characteristics, thereby reducing the error of localization. The proposed system is composed of only a commercially available PC, and exhibits good tracking performances with processing rate of full video frames.
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