Monocular Pedestrian Detection: Survey and Experiments

Heidelberg University · Daimler (Germany) · +1 more institution

PubMed
Indexed incrossrefpubmed

Abstract

Pedestrian detection is a rapidly evolving area in computer vision with key applications in intelligent vehicles, surveillance, and advanced robotics. The objective of this paper is to provide an overview of the current state of the art from both methodological and experimental perspectives. The first part of the paper consists of a survey. We cover the main components of a pedestrian detection system and the underlying models. The second (and larger) part of the paper contains a corresponding experimental study. We consider a diverse set of state-of-the-art systems: wavelet-based AdaBoost cascade [74], HOG/linSVM [11], NN/LRF [75], and combined shape-texture detection [23]. Experiments are performed on an…

Citation impact

1,226
total citations
FWCI
55.37
Percentile
100%
References
83
Citations per year

Authors

2

Topics & keywords

Keywords
  • Artificial intelligence
  • Pedestrian detection
  • Computer vision
  • Computer science
  • Pedestrian
  • Object detection
  • Monocular vision
  • Monocular
UN Sustainable Development Goals
  • Sustainable cities and communities
No related works found for this paper.

Funding