Sensor fusion based obstacle detection/classification for active pedestrian protection system

Ho Gi Jung, Yun Hee Lee, Pal Joo Yoon, In Yong Hwang, Jaihie Kim

Research output: Contribution to journalConference articlepeer-review

14 Citations (Scopus)


This paper proposes a sensor fusion based obstacle detection/classification system for active pedestrian protection system. At the frontend of vehicle, one laser scanner and one camera is installed. Clustering and tracking of range data from laser scanner generate obstacle candidates. Vision system classifies the candidates into three categories: pedestrian, vehicle, and other. Gabor filter bank extracts the feature vector of candidate image. The obstacle classification is implemented by combining two classifiers with the same architecture: support vector machine for pedestrian and vehicle. Obstacle detection system recognizing the class can actively protect pedestrian while reducing false positive rate.

Original languageEnglish
Pages (from-to)294-305
Number of pages12
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4292 LNCS - II
Publication statusPublished - 2006
Event2nd International Symposium on Visual Computing, ISVC 2006 - Lake Tahoe, NV, United States
Duration: 2006 Nov 62006 Nov 8

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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