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» Learning a Sparse Representation for Object Detection
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Publication
383views
15 years 9 months ago
Hunting Nessie -- Real-Time Abnormality Detection from Webcams
We present a data-driven, unsupervised method for unusual scene detection from static webcams. Such time-lapse data is usually captured with very low or varying framerate. This ...
Michael D. Breitenstein, Helmut Grabner, Luc Van G...
NIPS
2008
14 years 11 months ago
Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree
Unexpected stimuli are a challenge to any machine learning algorithm. Here we identify distinct types of unexpected events, focusing on 'incongruent events' when 'g...
Daphna Weinshall, Hynek Hermansky, Alon Zweig, Jie...
CVPR
2006
IEEE
15 years 11 months ago
A Design Principle for Coarse-to-Fine Classification
Coarse-to-fine classification is an efficient way of organizing object recognition in order to accommodate a large number of possible hypotheses and to systematically exploit shar...
Sachin Gangaputra, Donald Geman
CVIU
2007
146views more  CVIU 2007»
14 years 9 months ago
Face detection in gray scale images using locally linear embeddings
The problem of face detection remains challenging because faces are non-rigid objects that have a high degree of variability with respect to head rotation, illumination, facial ex...
Samuel Kadoury, Martin D. Levine
ICRA
2010
IEEE
170views Robotics» more  ICRA 2010»
14 years 8 months ago
Categorizing object-action relations from semantic scene graphs
— In this work we introduce a novel approach for detecting spatiotemporal object-action relations, leading to both, action recognition and object categorization. Semantic scene g...
Eren Erdal Aksoy, Alexey Abramov, Florentin Wö...