Research on Three-Dimensional "High Presence Relay" System
| Project/Area Number |
18500131
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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 | Wakayama University |
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Principal Investigator |
WU Haiyuan Wakayama University, Faculty of Systems Engineering, Professor (70283695)
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| Co-Investigator(Kenkyū-buntansha) |
CHEN Qian Wakayama University, Faculty of Systems Engineering, Associate Professor (70263233)
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| Project Period (FY) |
2006 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥330,000)
Fiscal Year 2007: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2006: ¥2,600,000 (Direct Cost: ¥2,600,000)
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| Keywords | High presence relay / Video rate / Target tracking / Active camera / Three-dimensional |
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| Research Abstract |
A) In this research, we propose a K-means clustering based target tracking algorithm (called as K-means tracker), which can work robustly when tracking an object with hole through which the background can be seen (e.g. mosquito coil). The contributions of this research include: 1) Using a 5D feature vector to represent both the color "Y,U,V" and geometric "x,y" features of each pixel uniformly. This enables the simultaneous adaptation to both the color and geometric features during tracking; 2) Using a variable ellipse model to describe the search area and model the surrounding background. This guarantees the stable object tracking under various geometric transformations; 3) Achieving the automatic self tracking failure detection and recovery with both the "target" and "background" samples. Moreover, we propose a reliability-based K-means clustering algorithm (called as RK-means tracker) to remove the noise background pixel (which is neither similar to the target nor the background sam
… More
ples) from the target object. According to the triangular relationship among an unknown pixel and its two nearest cluster centers (target and background), the normal pixel (target or background one) will be assigned with high reliability value and correctly classified, while noise pixels will be given low reliability value and ignored. A radial sampling method is also brought out for improving both the processing speed and the robustness of this algorithm.
B) In this research, we propose a high-performance object tracking system for obtaining high-quality images of a high-speed moving object at video rate by controlling a Fixed Viewpoint Pan Tilt Camera (FV-PTZ Camera) . To achieve our goal, we use the K-means tracker algorithm for tracking objects in an image sequence captured by the active cameras. We use the results of the K-means tracker to control the angular position and speed of each pan-tilt-zoom unit by employing the PID control scheme. Moreover, by using two cameras, the binocular stereo vision algorithm can be used to obtain the 3D position and velocity of the object. These results are used in order to adjust the focus and zoom. Our system allows the two cameras to gaze at a single point in 3D space. However, this system may become unstable when the time response deteriorates by excessively interfering in a mutual control loop or by strict restriction of the camera action. In order to solve these problems, we introduce the concept of reliability into the K-means tracker, and propose a method for controlling the active cameras by using relative reliability. Less
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Report
(3 results)
Research Products
(70 results)
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[Journal Article] 高速追従型能動カメラシステム2007
Author(s)
大池洋史, 呉海元, 華春生, 和田俊和
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Journal Title
システム制御情報学会論文誌 Vol.20,No.3
Pages: 114-121
NAID
Description
「研究成果報告書概要(和文)」より
Related Report
Peer Reviewed
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[Presentation] Detection and Tracking using Multi Color Target Models2007
Author(s)
H. Oike, Toshikazu, Wada, T. Iizuka, Haiyuan, Wu, T. Mitashita, N. Hagita
Organizer
Proc. of SPIE (SPIE Optics East), the international society for optical engineering, Proc of Intelligent Robots and Computer Vision XXV: Algorithms, Techniques, and Active Vision
Description
「研究成果報告書概要(欧文)」より
Related Report
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