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» Resampling methods for input modeling
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105
Voted
CVPR
2005
IEEE
16 years 4 months ago
Bayesian 3D Modeling from Images Using Multiple Depth Maps
This paper addresses the problem of reconstructing the geometry and color of a Lambertian scene, given some fully calibrated images acquired with wide baselines. In order to compl...
Pau Gargallo, Peter F. Sturm
136
Voted
CVPR
2008
IEEE
16 years 4 months ago
Discriminative human action segmentation and recognition using semi-Markov model
Given an input video sequence of one person conducting a sequence of continuous actions, we consider the problem of jointly segmenting and recognizing actions. We propose a discri...
Qinfeng Shi, Li Wang, Li Cheng, Alexander J. Smola
116
Voted
ICPR
2000
IEEE
16 years 3 months ago
Precise Hand-printed Character Recognition Using Elastic Models via Nonlinear Transformation
Distorted character recognition is a difficult but inevitable problem in hand-printed character recognition. In this paper, we propose a character recognition method using elastic...
Tsuyoshi Kato, Shinichiro Omachi, Hirotomo Aso
CORR
2012
Springer
232views Education» more  CORR 2012»
13 years 10 months ago
Smoothing Proximal Gradient Method for General Structured Sparse Learning
We study the problem of learning high dimensional regression models regularized by a structured-sparsity-inducing penalty that encodes prior structural information on either input...
Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbone...
106
Voted
ICCS
2005
Springer
15 years 8 months ago
Dynamic Data Driven Coupling of Continuous and Discrete Methods for 3D Tracking
We present a new framework for robust 3D tracking, using a dynamic data driven coupling of continuous and discrete methods to overcome their limitations. Our method uses primarily ...
Dimitris N. Metaxas, Gabriel Tsechpenakis