Search Results - "2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)"

Histograms of oriented gradients for human detection by Dalal, N., Triggs, B.

“…We study the question of feature sets for robust visual object recognition; adopting linear SVM based human detection as a test case. After reviewing existing…”
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A non-local algorithm for image denoising by Buades, A., Coll, B., Morel, J.-M.

“…We propose a new measure, the method noise, to evaluate and compare the performance of digital image denoising methods. We first compute and analyze this…”
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Learning a similarity metric discriminatively, with application to face verification by Chopra, S., Hadsell, R., LeCun, Y.

“…We present a method for training a similarity metric from data. The method can be used for recognition or verification applications where the number of…”
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Accurate and efficient stereo processing by semi-global matching and mutual information by Hirschmuller, H.

“…This paper considers the objectives of accurate stereo matching, especially at object boundaries, robustness against recording or illumination changes and…”
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Overview of the face recognition grand challenge by Phillips, P.J., Flynn, P.J., Scruggs, T., Bowyer, K.W., Jin Chang, Hoffman, K., Marques, J., Jaesik Min, Worek, W.

“…Over the last couple of years, face recognition researchers have been developing new techniques. These developments are being fueled by advances in computer…”
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Level set evolution without re-initialization: a new variational formulation by Chunming Li, Chenyang Xu, Changfeng Gui, Fox, M.D.

“…In this paper, we present a new variational formulation for geometric active contours that forces the level set function to be close to a signed distance…”
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Matching with PROSAC - progressive sample consensus by Chum, O., Matas, J.

“…A new robust matching method is proposed. The progressive sample consensus (PROSAC) algorithm exploits the linear ordering defined on the set of…”
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A Bayesian hierarchical model for learning natural scene categories by Fei-Fei, L., Perona, P.

“…We propose a novel approach to learn and recognize natural scene categories. Unlike previous work, it does not require experts to annotate the training set. We…”
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Fields of Experts: a framework for learning image priors by Roth, S., Black, M.J.

“…We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine…”
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ARTag, a fiducial marker system using digital techniques by Fiala, M.

“…Fiducial marker systems consist of patterns that are mounted in the environment and automatically detected in digital camera images using an accompanying…”
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Shape matching and object recognition using low distortion correspondences by Berg, A.C., Berg, T.L., Malik, J.

“…We approach recognition in the framework of deformable shape matching, relying on a new algorithm for finding correspondences between feature points. This…”
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Pedestrian detection in crowded scenes by Leibe, B., Seemann, E., Schiele, B.

“…In this paper, we address the problem of detecting pedestrians in crowded real-world scenes with severe overlaps. Our basic premise is that this problem is too…”
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Object recognition with features inspired by visual cortex by Serre, T., Wolf, L., Poggio, T.

“…We introduce a novel set of features for robust object recognition. Each element of this set is a complex feature obtained by combining position- and…”
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Integral histogram: a fast way to extract histograms in Cartesian spaces by Porikli, F.

“…We present a novel method, which we refer as an integral histogram, to compute the histograms of all possible target regions in a Cartesian data space. Our…”
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Spectral segmentation with multiscale graph decomposition by Cour, T., Benezit, F., Shi, J.

“…We present a multiscale spectral image segmentation algorithm. In contrast to most multiscale image processing, this algorithm works on multiple scales of the…”
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Local discriminant embedding and its variants by Hwann-Tzong Chen, Huang-Wei Chang, Tyng-Luh Liu

“…We present a new approach, called local discriminant embedding (LDE), to manifold learning and pattern classification. In our framework, the neighbor and class…”
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Recognizing facial expression: machine learning and application to spontaneous behavior by Bartlett, M.S., Littlewort, G., Frank, M., Lainscsek, C., Fasel, I., Movellan, J.

“…We present a systematic comparison of machine learning methods applied to the problem of fully automatic recognition of facial expressions. We report results…”
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Activity recognition and abnormality detection with the switching hidden semi-Markov model by Duong, T.V., Bui, H.H., Phung, D.Q., Venkatesh, S.

“…This paper addresses the problem of learning and recognizing human activities of daily living (ADL), which is an important research issue in building a…”
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Spatiograms versus histograms for region-based tracking by Birchfield, S.T., Sriram Rangarajan

“…We introduce the concept of a spatiogram, which is a generalization of a histogram that includes potentially higher order moments. A histogram is a…”
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Actions sketch: a novel action representation by Alper Yilmaz, Mubarak Shah

“…In this paper, we propose to model an action based on both the shape and the motion of the performing object. When the object performs an action in 3D, the…”
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