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ECCV
2004
Springer
14 years 6 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
ECAI
2008
Springer
13 years 6 months ago
Salience-driven Contextual Priming of Speech Recognition for Human-Robot Interaction
Abstract. The paper presents an implemented model for priming speech recognition, using contextual information about salient entities. The underlying hypothesis is that, in human-r...
Pierre Lison, Geert-Jan M. Kruijff
CORR
2010
Springer
108views Education» more  CORR 2010»
13 years 1 months ago
Affine Invariant, Model-Based Object Recognition Using Robust Metrics and Bayesian Statistics
We revisit the problem of model-based object recognition for intensity images and attempt to address some of the shortcomings of existing Bayesian methods, such as unsuitable prior...
Vasileios Zografos, Bernard F. Buxton
PR
2008
173views more  PR 2008»
13 years 4 months ago
Object recognition using a generalized robust invariant feature and Gestalt's law of proximity and similarity
In this paper, we propose a new context-based method for object recognition. We first introduce a neuro-physiologically motivated visual part detector. We found that the optimal f...
Sungho Kim, Kuk-Jin Yoon, In-So Kweon
ICCV
2001
IEEE
14 years 6 months ago
Statistical Context Priming for Object Detection
There is general consensus that context can be a rich source of information about an object's identity, location and scale. However, the issue of how to formalize contextual ...
Antonio B. Torralba, Pawan Sinha