DocumentCode :
691990
Title :
Matching of Laser Range Sensor Data and 3D Surface Scanner Data Robust to Abnormal Values Using Evolutionary ICP Algorithm and Gaussian Function
Author :
Nakajima, Shigeru
Author_Institution :
Grad. Sch. of Eng., Osaka City Univ., Osaka, Japan
fYear :
2013
fDate :
16-18 Oct. 2013
Firstpage :
250
Lastpage :
254
Abstract :
Recently need of surveillance systems are increasing for aging society or terrorism. People use image cameras, infra-red scanners or other equipments for surveillance. There are infra-red 2D range sensors with wide view angles and long distance. Also there are infra-red 3D scanners with narrow view angles and short distance. A surveillance system which is a combination of those equipments of the both types is expected to be useful. In this paper a method which is a combination of ES and ICP is proposed to match data of 2D range sensor and data of 3D scanner. The method uses Gaussian function as a fitness function to avoid an influence of abnormal data.
Keywords :
Gaussian processes; evolutionary computation; image matching; image sensors; infrared imaging; laser ranging; optical scanners; terrorism; video cameras; video surveillance; 3D infrared scanner; 3D surface scanner data; Gaussian function; abnormal value; aging society; evolutionary ICP algorithm; fitness function; image camera; infrared 2D range sensor; laser range sensor data matching; surveillance system; terrorism; view angle; Estimation; Iterative closest point algorithm; Robot sensing systems; Surface treatment; Surveillance; Three-dimensional displays; Gussian function; ICP; evolutional strategy; infra-red 3D scanner; infra-red range sensor; surveillance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Hiding and Multimedia Signal Processing, 2013 Ninth International Conference on
Conference_Location :
Beijing
Type :
conf
DOI :
10.1109/IIH-MSP.2013.71
Filename :
6846627
Link To Document :
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