articleOct 23, 2006GREEN OA

Visual attention detection in video sequences using spatiotemporal cues

University of Central Florida

Indexed incrossref

Abstract

Human vision system actively seeks interesting regions in images to reduce the search effort in tasks, such as object detection and recognition. Similarly, prominent actions in video sequences are more likely to attract our first sight than their surrounding neighbors. In this paper, we propose a spatiotemporal video attention detection technique for detecting the attended regions that correspond to both interesting objects and actions in video sequences. Both spatial and temporal saliency maps are constructed and further fused in a dynamic fashion to produce the overall spatiotemporal attention model. In the temporal attention model, motion contrast is computed based on the planar motions (homography) between…

Citation impact

966
total citations
FWCI
9.78
Percentile
100%
References
27
Citations per year

Authors

2

Topics & keywords

Keywords
  • Artificial intelligence
  • Computer vision
  • Computer science
  • Contrast (vision)
  • RANSAC
  • Optical flow
  • Histogram
  • Motion (physics)
UN Sustainable Development Goals
  • Reduced inequalities
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