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NIPS
2001
13 years 10 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona
ICCV
2011
IEEE
12 years 8 months ago
Automated Articulated Structure and 3D Shape Recovery from Point Correspondences
In this paper we propose a new method for the simultaneous segmentation and 3D reconstruction of interest point based articulated motion. We decompose a set of point tracks into r...
Joao Fayad, Chris Russell, Lourdes Agapito
PAMI
2012
11 years 11 months ago
Fast Joint Estimation of Silhouettes and Dense 3D Geometry from Multiple Images
—We propose a probabilistic formulation of joint silhouette extraction and 3D reconstruction given a series of calibrated 2D images. Instead of segmenting each image separately i...
Kalin Kolev, Thomas Brox, Daniel Cremers
BIBE
2007
IEEE
126views Bioinformatics» more  BIBE 2007»
13 years 10 months ago
An End-to-End Process for Cancer Identification from Images of Lung Tissue
— This research describes a non-interactive process that applies several forms of computational intelligence to the task of classifying biopsy lung tissue samples based on visual...
Walker H. Land Jr., Daniel W. McKee, Tatyana Zhuko...
CVIU
2006
110views more  CVIU 2006»
13 years 8 months ago
Simultaneous tracking of multiple body parts of interacting persons
This paper presents a framework to simultaneously segment and track multiple body parts of interacting humans in the presence of mutual occlusion and shadow. The framework uses mu...
Sangho Park, Jake K. Aggarwal