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» Computing Visual Attention from Scene Depth
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117
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ECCV
2004
Springer
16 years 2 months ago
Recognition by Probabilistic Hypothesis Construction
We present a probabilistic framework for recognizing objects in images of cluttered scenes. Hundreds of objects may be considered and searched in parallel. Each object is learned f...
Pierre Moreels, Michael Maire, Pietro Perona
VISUALIZATION
1996
IEEE
15 years 5 months ago
Hierarchical and Parallelizable Direct Volume Rendering for Irregular and Multiple Grids
A general volume rendering technique is described that efficiently produces images of excellent quality from data defined over irregular grids having a wide variety of formats. Re...
Jane Wilhelms, Allen Van Gelder, Paul Tarantino, J...
115
Voted
ICDE
2010
IEEE
252views Database» more  ICDE 2010»
16 years 16 days ago
Semantic Ranking and Result Visualization for Life Sciences Publications
An ever-increasing amount of data and semantic knowledge in the domain of life sciences is bringing about new data management challenges. In this paper we focus on adding the seman...
Julia Stoyanovich, Kenneth A. Ross, William Mee
94
Voted
FLAIRS
2004
15 years 2 months ago
VENUS: A System for Novelty Detection in Video Streams with Learning
Novelty detection in video is a rapidly developing application domain within computer vision. The motivation behind this paper is a learning based framework for detecting novelty ...
Roger S. Gaborski, Vishal S. Vaingankar, Vineet Ch...
IJCV
1998
135views more  IJCV 1998»
15 years 14 days ago
A Multibody Factorization Method for Independently Moving Objects
The structure-from-motion problem has been extensively studied in the field of computer vision. Yet, the bulk of the existing work assumes that the scene contains only a single mo...
João Paulo Costeira, Takeo Kanade