Integrating appearance and edge features for sedan vehicle detection in the blind-spot area

Bin Feng Lin*, Yi Ming Lin, Li Chen Fu, Pei Yung Hsiao, Li An Chuang, Shin Shinh Huang, Min Fang Lo

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

112 Scopus citations


Changing lanes while having no information about the blind spot area can be dangerous. We propose a vision-based vehicle detection system for a lane changing assistance system to monitor the potential sedan vehicle in the blind-spot area. To serve our purpose, we select adequate features, which are directly obtained from vehicle images, to detect possible vehicles in the blind-spot area. This is challenging due to the significant change in the view angle of a vehicle along with its location throughout the blind-spot area. To cope with this problem, we propose a method to combine two kinds of part-based features that are related to the characteristics of the vehicle, and we build multiple models based on different viewpoints of a vehicle. The location information of each feature is incorporated to help construct the detector and estimate the reasonable position of the presence of the vehicle. The experiments show that our system is reliable in detecting various sedan vehicles in the blind-spot area.

Original languageEnglish
Article number6145682
Pages (from-to)737-747
Number of pages11
JournalIEEE Transactions on Intelligent Transportation Systems
Issue number2
StatePublished - 2012
Externally publishedYes


  • Blind-spot area
  • feature integration
  • spatial relationship
  • vehicle detection


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