Title :
Optimal sensor planning with minimal cost for 3D object recognition using sparse structured light images
Author :
Lin, Xueyin ; Zeng, Jianchao ; Yao, Qixiang
Author_Institution :
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
Abstract :
A novel 3D CAD-based vision system by using sparse structured light images is presented in this paper. By using an eye-on-hand structured light sensor, sparse range images are collected from several different positions based upon the requirements in the process of object recognition and localization. In order to recognize object with minimal sensing activities, a novel concept of maximum expected rate of hypothesis reduction (MERHR) for sensor planning is proposed its implementational procedure is carefully designed. By pre-computing the sensor´s optimal configuration and storing it into a lookup table, the heavy computation burden for sensor planning during on-line recognition phase can be avoided
Keywords :
CAD; feature extraction; image sensors; object recognition; optical sensors; 3D CAD-based vision system; 3D object recognition; eye-on-hand structured light sensor; maximum expected rate of hypothesis reduction; minimal cost; optimal configuration; optimal sensor planning; sparse range images; sparse structured light images; Cost function; Feature extraction; Image sensors; Machine vision; Mechanical sensors; Object recognition; Sensor systems; Strategic planning; Table lookup; Technology planning;
Conference_Titel :
Robotics and Automation, 1996. Proceedings., 1996 IEEE International Conference on
Conference_Location :
Minneapolis, MN
Print_ISBN :
0-7803-2988-0
DOI :
10.1109/ROBOT.1996.509243
