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» Learning Models for Object Recognition
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CVPR
2007
IEEE
14 years 11 months ago
Joint Object Segmentation and Behavior Classification in Image Sequences
In this paper, we propose a general framework for fusing bottom-up segmentation with top-down object behavior classification over an image sequence. This approach is beneficial fo...
Laura Gui, Jean-Philippe Thiran, Nikos Paragios
RSS
2007
145views Robotics» more  RSS 2007»
13 years 10 months ago
Semantic Modeling of Places using Objects
— While robot mapping has seen massive strides , higher level abstractions in map representation are still not widespread. Maps containing semantic concepts such as objects and l...
Ananth Ranganathan, Frank Dellaert
ICPR
2010
IEEE
14 years 10 days ago
The Fusion of Deep Learning Architectures and Particle Filtering Applied to Lip Tracking
This work introduces a new pattern recognition model for segmenting and tracking lip contours in video sequences. We formulate the problem as a general nonrigid object tracking me...
Gustavo Carneiro, Jacinto Nascimento
ICCV
2009
IEEE
13 years 6 months ago
Efficient multi-label ranking for multi-class learning: Application to object recognition
Multi-label learning is useful in visual object recognition when several objects are present in an image. Conventional approaches implement multi-label learning as a set of binary...
Serhat Selcuk Bucak, Pavan Kumar Mallapragada, Ron...
BMVC
1998
13 years 10 months ago
ORASSYLL: Object Recognition with Autonomously Learned and Sparse Symbolic Representations Based on Local Line Detectors
We introduce an object recognition system in which objects are represented as a sparse and spatially organized set of local (bent) line segments. The line segments correspond to b...
Norbert Krüger, Niklas Lüdtke