Detection and classification of vehicles

University of Minnesota

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Abstract

This paper presents algorithms for vision-based detection and classification of vehicles in monocular image sequences of traffic scenes recorded by a stationary camera. Processing is done at three levels: raw images, region level, and vehicle level. Vehicles are modeled as rectangular patches with certain dynamic behavior. The proposed method is based on the establishment of correspondences between regions and vehicles, as the vehicles move through the image sequence. Experimental results from highway scenes are provided which demonstrate the effectiveness of the method. We also briefly describe an interactive camera calibration tool that we have developed for recovering the camera parameters using features in…

Citation impact

806
total citations
FWCI
12.84
Percentile
100%
References
17
Citations per year

Authors

4

Topics & keywords

Keywords
  • Computer vision
  • Artificial intelligence
  • Computer science
  • Camera resectioning
  • Monocular vision
  • Calibration
  • Monocular
  • Image (mathematics)
UN Sustainable Development Goals
  • Sustainable cities and communities
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