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IJCV
2000
136views more  IJCV 2000»
14 years 11 months ago
A Trainable System for Object Detection
This paper presents a general, trainable system for object detection in unconstrained, cluttered scenes. The system derives much of its power from a representation that describes a...
Constantine Papageorgiou, Tomaso Poggio
ICPR
2006
IEEE
16 years 26 days ago
A Model-based Approach for Rigid Object Recognition
Most object recognition systems require large databases of real images for classifier training. To collect real images for this purpose is a difficult and expensive process. This ...
Chee Boon Chong, Fee-Lee Lim, Tele Tan
IPPS
2007
IEEE
15 years 6 months ago
VoroNet: A scalable object network based on Voronoi tessellations
In this paper, we propose the design of VoroNet, an objectbased peer to peer overlay network relying on Voronoi tessellations, along with its theoretical analysis and experimental...
Olivier Beaumont, Anne-Marie Kermarrec, Loris Marc...
DEXA
2006
Springer
116views Database» more  DEXA 2006»
15 years 1 months ago
Interpolating and Using Most Likely Trajectories in Moving-Objects Databases
In recent years, many emerging database applications deal with large sets of continuously moving data objects. Since no computer system can commit continuously occurring infinitesi...
Byunggu Yu, Seon Ho Kim
NIPS
2004
15 years 1 months ago
Contextual Models for Object Detection Using Boosted Random Fields
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
Antonio Torralba, Kevin P. Murphy, William T. Free...