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» RGB-(D) scene labeling: Features and algorithms
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PAMI
2008
302views more  PAMI 2008»
13 years 7 months ago
Learning to Detect Moving Shadows in Dynamic Environments
We propose a novel adaptive technique for detecting moving shadows and distinguishing them from moving objects in video sequences. Most methods for detecting shadows work in a stat...
Ajay J. Joshi, Nikolaos Papanikolopoulos
CVPR
2008
IEEE
14 years 9 months ago
Recognition by association via learning per-exemplar distances
We pose the recognition problem as data association. In this setting, a novel object is explained solely in terms of a small set of exemplar objects to which it is visually simila...
Tomasz Malisiewicz, Alexei A. Efros
ACCV
2010
Springer
13 years 2 months ago
Efficient Structured Support Vector Regression
Support Vector Regression (SVR) has been a long standing problem in machine learning, and gains its popularity on various computer vision tasks. In this paper, we propose a structu...
Ke Jia, Lei Wang, Nianjun Liu
ECCV
2004
Springer
14 years 9 months ago
A Statistical Model for General Contextual Object Recognition
We consider object recognition as the process of attaching meaningful labels to specific regions of an image, and propose a model that learns spatial relationships between objects....
Peter Carbonetto, Nando de Freitas, Kobus Barnard
KAIS
2006
172views more  KAIS 2006»
13 years 7 months ago
CoMMA: a framework for integrated multimedia mining using multi-relational associations
Generating captions or annotations automatically for still images is a challenging task. Traditionally, techniques involving higher-level (semantic) object detection and complex f...
Ankur Teredesai, Muhammad A. Ahmad, Juveria Kanodi...