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» RGB-(D) scene labeling: Features and algorithms
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PAMI
2008
302views more  PAMI 2008»
13 years 5 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 7 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 12 days 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 7 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 5 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...