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CVPR
2008
IEEE
14 years 10 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
PR
2008
228views more  PR 2008»
13 years 8 months ago
Accurate integration of multi-view range images using k-means clustering
3D modelling finds a wide range of applications in industry. However, due to the presence of surface scanning noise, accumulative registration errors, and improper data fusion, re...
Hong Zhou, Yonghuai Liu
IROS
2007
IEEE
157views Robotics» more  IROS 2007»
14 years 2 months ago
A spatio-temporal probabilistic model for multi-sensor object recognition
— This paper presents a general framework for multi-sensor object recognition through a discriminative probabilistic approach modelling spatial and temporal correlations. The alg...
Bertrand Douillard, Dieter Fox, Fabio T. Ramos
ECCV
2008
Springer
14 years 10 months ago
A Probabilistic Cascade of Detectors for Individual Object Recognition
A probabilistic system for recognition of individual objects is presented. The objects to recognize are composed of constellations of features, and features from a same object shar...
Pierre Moreels, Pietro Perona
ICMCS
2005
IEEE
90views Multimedia» more  ICMCS 2005»
14 years 2 months ago
Eye Detection Under Unconstrained Background by the Terrain Feature
Locating eyes in face images is an important step for automatic face analysis and recognition. In this paper, we present a novel approach for eye detection without finding the fa...
Jun Wang, Lijun Yin