Results 1 - 10
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146
Unsupervised Learning of Image Manifolds by Semidefinite Programming
, 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 ..."
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Cited by 270 (9 self)
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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
"... 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
"... 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 ..."
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Cited by 147 (23 self)
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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
- 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 ..."
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Cited by 1 (0 self)
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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
- 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 ..."
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Cited by 84 (16 self)
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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
"... 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
"... 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 ..."
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Cited by 2 (1 self)
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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
"... 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 ..."
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Cited by 4 (2 self)
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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
- 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 ..."
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Cited by 10 (4 self)
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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
, 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 ..."
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Cited by 14 (1 self)
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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