Dokument öffnen
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Allgemeine Angaben |
| Autor |
Yang, Yang; Cao, Qixin |
| Erschienen |
InTech Open Access Publisher, 2013
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| Ausgabe |
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| Umfang |
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| ISBN |
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| Kurzbeschreibung |
In this paper, we propose a fast feature
points‐based object tracking method for robot grasp. In
the detection phase, we detect the object with SIFT
feature points extraction and matching. Then we
compute the object’s image position with homography
constraints and set up an interest window to
accommodate the object. In the tracking phase, we only
focus on the interest window, detecting feature points
from the window and updating the window’s position
and size. Our method is of special practical meaning in
the case of service robot grasp. Because when the robot
grasps the object, the object’s image size is usually
small relative to the whole image, it is unnecessary to
detect the whole image. On the other hand, the object
is partially occluded by the robot gripper. SIFT is good
at dealing with occlusion, but it is time consuming.
Hence, by combining SIFT and an interest window, our
method gains the ability to deal with occlusion and can
satisfy the real‐time requirements at the same time.
Experiments show that our method exceeds several
leading feature points‐based object tracking methods
in real‐time performance. |
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International Journal of Advanced Robotic Systems
Autor: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Erschienen: 2004
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