Depth Cue Integration
Depth Cue Integration is a computational process in visual perception research that combines multiple sources of depth information, such as binocular disparity, motion parallax, and pictorial cues, to form a unified and coherent estimate of three-dimensional scene structure.
114
Publications
7.5K
Citations
291
Authors
159
Institutions
Publications per year
2017–2026
19
Parents
114
Contrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection
Jiaxing Zhao, Yang Cao, Deng-Ping Fan et al. · 2019 · 437 citations
Slant from texture and disparity cues: Optimal cue combination
James Hillis, Simon J. Watt, Michael S. Landy et al. · Journal of Vision · 2004 · 433 citations · Full text
Optimal integration of texture and motion cues to depth
Robert A. Jacobs · Vision Research · 1999 · 339 citations
Medicine, Psychology, Vision Science +17
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Brown University
Providence, United States
7 h-index
11 publications
202 citations

University of Birmingham
Birmingham, United Kingdom
6 h-index
16 publications
1K citations

York University
Toronto, Canada
5 h-index
10 publications
425 citations

University of Rochester
Rochester, United States
5 h-index
6 publications
756 citations
Max Planck Institute for Biological Cybernetics
Tübingen, Germany
5 h-index
12 publications
1.9K citations
Harvard University
Cambridge, United States
5 h-index
6 publications
577 citations
New York University
New York, United States
5 h-index
11 publications
1.7K citations
University of Florence
Florence, Italy
4 h-index
4 publications
86 citations
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17 publications · 1.3K citations
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11 publications · 1.2K citations
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5 publications · 261 citations
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5 publications · 234 citations
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4 publications · 532 citations
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