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» Object Recognition using Junctions
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ECCV
2004
Springer
15 years 12 months ago
Recognition by Probabilistic Hypothesis Construction
We present a probabilistic framework for recognizing objects in images of cluttered scenes. Hundreds of objects may be considered and searched in parallel. Each object is learned f...
Pierre Moreels, Michael Maire, Pietro Perona
ACCV
2006
Springer
15 years 4 months ago
Biologically Motivated Perceptual Feature: Generalized Robust Invariant Feature
Abstract. In this paper, we present a new, biologically inspired perceptual feature to solve the selectivity and invariance issue in object recognition. Based on the recent findin...
Sungho Kim, In-So Kweon
PR
2007
143views more  PR 2007»
14 years 9 months ago
Shadow resistant tracking using inertia constraints
In this paper, we present a new method for tracking objects with shadows. Traditional motion-based tracking schemes cannot usually distinguish the shadow from the object itself, a...
Hao Jiang, Mark S. Drew
ECCV
2000
Springer
15 years 12 months ago
Unsupervised Learning of Models for Recognition
We present a method to learn object class models from unlabeled and unsegmented cluttered scenes for the purpose of visual object recognition. We focus on a particular type of mode...
Markus Weber, Max Welling, Pietro Perona
AVSS
2005
IEEE
15 years 3 months ago
Shape recognition based on a video and multi-sensor system
We present in this paper a real-time system for shape recognition. The proposed system is a video and multisensor platform that is able to classify the mobile objects evolving in ...
Huy-Binh Bui Ngoc, François Brémond,...