Pedestrian Detection: An Evaluation of the State of the Art

California Institute of Technology · Max Planck Institute for Informatics · +1 more institution

PubMed
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Abstract

Pedestrian detection is a key problem in computer vision, with several applications that have the potential to positively impact quality of life. In recent years, the number of approaches to detecting pedestrians in monocular images has grown steadily. However, multiple data sets and widely varying evaluation protocols are used, making direct comparisons difficult. To address these shortcomings, we perform an extensive evaluation of the state of the art in a unified framework. We make three primary contributions: 1) We put together a large, well-annotated, and realistic monocular pedestrian detection data set and study the statistics of the size, position, and occlusion patterns of pedestrians in urban scenes,…

Citation impact

3,244
total citations
FWCI
115.37
Percentile
100%
References
99
Citations per year

Authors

4

Topics & keywords

Keywords
  • Pedestrian detection
  • Computer science
  • Pedestrian
  • Artificial intelligence
  • Frame (networking)
  • Computer vision
  • Monocular
  • Key (lock)
UN Sustainable Development Goals
  • Sustainable cities and communities
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