Results 1 - 10 of 146

Unsupervised Learning of Image Manifolds by Semidefinite Programming

by Kilian Q. Weinberger , Lawrence K. Saul , 2004
"... Can we detect low dimensional structure in high dimensional data sets of images and video? The problem of dimensionality reduction arises often in computer vision and pattern recognition. In this paper, we propose a new solution to this problem based on semidefinite programming. Our algorithm can be ..."
Abstract - Cited by 270 (9 self) - Add to MetaCart
Can we detect low dimensional structure in high dimensional data sets of images and video? The problem of dimensionality reduction arises often in computer vision and pattern recognition. In this paper, we propose a new solution to this problem based on semidefinite programming. Our algorithm can

Manifold Learning for Video-to-Video Face Recognition

by unknown authors
"... Abstract. We look in this work at the problem of video-based face recognition in which both training and test sets are video sequences, and propose a novel approach based on manifold learning. The idea consists of first learning the intrinsic personal characteristics of each subject from the trainin ..."
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Abstract. We look in this work at the problem of video-based face recognition in which both training and test sets are video sequences, and propose a novel approach based on manifold learning. The idea consists of first learning the intrinsic personal characteristics of each subject from

Automatic Recognition of Facial Actions in Spontaneous Expressions

by Marian Stewart Bartlett, Gwen C. Littlewort, Mark G. Frank, Claudia Lainscsek, Ian R. Fasel, Javier R. Movellan
"... Abstract — Spontaneous facial expressions differ from posed expressions in both which muscles are moved, and in the dynamics of the movement. Advances in the field of automatic facial expression measurement will require development and assessment on spontaneous behavior. Here we present preliminary ..."
Abstract - Cited by 147 (23 self) - Add to MetaCart
results on a task of facial action detection in spontaneous facial expressions. We employ a user independent fully automatic system for real time recognition of facial actions from the Facial Action Coding System (FACS). The system automatically detects frontal faces in the video stream and coded each

Video face recognition with graphbased semi-supervised learning

by Effrosyni Kokiopoulou, Pascal Frossard - in Proc. ICME, 2009
"... We consider the problem of classification of multiple observations of the same object, possibly under different transformations. We view this problem as a special case of semi-supervised learning where all unlabelled examples belong to the same unknown class. We propose a low complexity solution tha ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
that fall short of exploiting the manifold structure of the face image data sets. Index Terms — Semi-supervised learning, label propagation, video-based face recognition.

Visual event recognition in videos by learning from web data

by Lixin Duan, Dong Xu, Ivor W. Tsang, Jiebo Luo - In CVPR. IEEE , 2010
"... We propose a visual event recognition framework for consumer domain videos by leveraging a large amount of loosely labeled web videos (e.g., from YouTube). First, we propose a new aligned space-time pyramid matching method to measure the distances between two video clips, where each video clip is di ..."
Abstract - Cited by 84 (16 self) - Add to MetaCart
We propose a visual event recognition framework for consumer domain videos by leveraging a large amount of loosely labeled web videos (e.g., from YouTube). First, we propose a new aligned space-time pyramid matching method to measure the distances between two video clips, where each video clip

Face Recognition in Videos by Label Propagation

by Vijay Kumar, Anoop M. Namboodiri, C. V. Jawahar
"... Abstract—We consider the problem of automatic identification of faces in videos such as movies, given a dictionary of known faces from a public or an alternate database. This has applications in video indexing, content based search, surveillance, and real time recognition on wearable computers. We p ..."
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propose a two stage approach for this problem. First, we recognize the faces in a video using a sparse representation framework using l1-minimization and select a few key-frames based on a robust confidence measure. We then use transductive learning to propagate the labels from the key

Learning Neighborhood Discriminative Manifolds for Video-based Face Recognition

by John See, Mohammad Faizal, Ahmad Fauzi
"... Abstract. In this paper, we propose a new supervised Neighborhood Discriminative Manifold Projection (NDMP) method for feature extrac-tion in video-based face recognition. The abundance of data in videos often result in highly nonlinear appearance manifolds. In order to ex-tract good discriminative ..."
Abstract - Cited by 2 (1 self) - Add to MetaCart
Abstract. In this paper, we propose a new supervised Neighborhood Discriminative Manifold Projection (NDMP) method for feature extrac-tion in video-based face recognition. The abundance of data in videos often result in highly nonlinear appearance manifolds. In order to ex-tract good discriminative

Neighborhood Discriminative Manifold Projection for Face Recognition in Video

by John See, Mohammad Faizal, Ahmad Fauzi
"... Abstract — This paper presents a novel supervised manifold learning method called Neighborhood Discriminative Manifold Projection (NDMP) for face recognition in video. By constructing a discriminative eigenspace projection of the high-dimensional face manifold, NDMP seeks to learn an optimal low-dim ..."
Abstract - Cited by 4 (2 self) - Add to MetaCart
Abstract — This paper presents a novel supervised manifold learning method called Neighborhood Discriminative Manifold Projection (NDMP) for face recognition in video. By constructing a discriminative eigenspace projection of the high-dimensional face manifold, NDMP seeks to learn an optimal low

Selecting models from videos for appearance-based face recognition

by Abdenour Hadid, Matti Pietikäinen - In Proc. the 17th International Conference on Pattern Recognition , 2004
"... In this paper, we propose an unsupervised approach to select representative face samples (models) from raw videos and build an appearance-based face recognition system. The approach is based on representing the face manifold in a low-dimensional space using the Locally Linear Embedding (LLE) algorit ..."
Abstract - Cited by 10 (4 self) - Add to MetaCart
In this paper, we propose an unsupervised approach to select representative face samples (models) from raw videos and build an appearance-based face recognition system. The approach is based on representing the face manifold in a low-dimensional space using the Locally Linear Embedding (LLE

Spatio-temporal Embedding for Statistical Face Recognition from Video. ECCV

by Wei Liu, Zhifeng Li, Xiaoou Tang , 2006
"... Abstract. This paper addresses the problem of how to learn an appropriate feature representation from video to benefit video-based face recognition. By simultaneously exploiting the spatial and temporal information, the problem is posed as learning Spatio-Temporal Embedding (STE) from raw video. STE ..."
Abstract - Cited by 14 (1 self) - Add to MetaCart
Abstract. This paper addresses the problem of how to learn an appropriate feature representation from video to benefit video-based face recognition. By simultaneously exploiting the spatial and temporal information, the problem is posed as learning Spatio-Temporal Embedding (STE) from raw video
Results 1 - 10 of 146