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» Computing Visual Attention from Scene Depth
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CVPR
2010
IEEE
15 years 25 days ago
Real-time Tracking of Multiple Occluding Objects using Level Sets
We derive a probabilistic framework for robust, realtime, visual tracking of multiple previously unseen objects from a moving camera. This framework models the discrete depth orde...
Charles Bibby, Ian Reid
ACCV
2007
Springer
15 years 3 months ago
Depth from Stationary Blur with Adaptive Filtering
This work achieves an efficient acquisition of scenes and their depths along long streets. A camera is mounted on a vehicle moving along a path and a sampling line properly set in ...
Jiang Yu Zheng, Min Shi
ICIP
2003
IEEE
15 years 3 months ago
Evolutionary design of context-free attentional operators
A framework for simulating the visual attention system in primates is presented. Each stage of the attentional hierarchy is chosen with consideration for both psychophysics and ma...
Neil D. B. Bruce, M. Ed Jernigan
IJCV
2007
210views more  IJCV 2007»
14 years 9 months ago
A Behavioral Analysis of Computational Models of Visual Attention
Robots often incorporate computational models of visual attention to streamline processing. Even though the number of visual attention systems employed on robots has increased dram...
Frederick Shic, Brian Scassellati
ECCV
2010
Springer
14 years 10 months ago
Semantic Segmentation of Urban Scenes Using Dense Depth Maps
In this paper we present a framework for semantic scene parsing and object recognition based on dense depth maps. Five viewindependent 3D features that vary with object class are e...
Chenxi Zhang, Liang Wang, Ruigang Yang