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» Geodesic Object Representation and Recognition
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ICPR
2008
IEEE
16 years 4 months ago
Illumination invariants based on Markov random fields
We propose textural features, which are invariant to illumination spectrum and extremely robust to illumination direction. They require only a single training image per texture an...
Pavel Vacha, Michal Haindl
CVPR
2007
IEEE
16 years 5 months ago
Learning and Matching Line Aspects for Articulated Objects
Traditional aspect graphs are topology-based and are impractical for articulated objects. In this work we learn a small number of aspects, or prototypical views, from video data. ...
Xiaofeng Ren
SCALESPACE
2001
Springer
15 years 8 months ago
A Multi-scale Feature Likelihood Map for Direct Evaluation of Object Hypotheses
This paper develops and investigates a new approach for evaluating feature based object hypotheses in a direct way. The idea is to compute a feature likelihood map (FLM), which is ...
Ivan Laptev, Tony Lindeberg
ICPR
2006
IEEE
16 years 4 months ago
Object Localization Using Input/Output Recursive Neural Networks
Localizing objects in images is a difficult task and represents the first step to the solution of the object recognition problem. This paper presents a novel approach to the local...
Lorenzo Sarti, Marco Maggini, Monica Bianchini
CVPR
2012
IEEE
13 years 6 months ago
Detecting activities of daily living in first-person camera views
We present a novel dataset and novel algorithms for the problem of detecting activities of daily living (ADL) in firstperson camera views. We have collected a dataset of 1 millio...
Hamed Pirsiavash, Deva Ramanan