Title :
Multi-Classifier Based LIDAR and Camera Fusion
Author :
Hwang, Jae Pil ; Cho, Seung Eun ; Ryu, Kyung Jin ; Park, Seungkeun ; Kim, Euntai
Author_Institution :
Yonsei Univ., Seoul
fDate :
Sept. 30 2007-Oct. 3 2007
Abstract :
We present a sensor fusion system using lidar and camera. We separate the system into two part which is hypothesis generation part and hypothesis verification part. These parts use different single sensors. Hypothesis generation is done using the lidar and hypothesis verification is done using the camera image. In hypothesis generation, we cluster the lidar data and do a perspective mapping to generate the candidate. In hypothesis verification, we used 5-SVMs classifier. Based on the candidate position, the candidate is putted in different SVM. In the result, we compared the result between 5-SVM hypothesis verification and single SVM hypothesis verification. The result showed 2.2% improvement.
Keywords :
cameras; image classification; image fusion; optical radar; radar imaging; support vector machines; 5-SVM classifier; LIDAR; camera image fusion; hypothesis generation; hypothesis verification; multiclassifier; sensor fusion system; support vector machine; Educational institutions; Fusion power generation; Intelligent transportation systems; Laser radar; Sensor fusion; Sensor systems; Smart cameras; Support vector machine classification; Support vector machines; Vehicle detection;
Conference_Titel :
Intelligent Transportation Systems Conference, 2007. ITSC 2007. IEEE
Conference_Location :
Seattle, WA
Print_ISBN :
978-1-4244-1396-6
Electronic_ISBN :
978-1-4244-1396-6
DOI :
10.1109/ITSC.2007.4357683