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Author Hamdi Dibeklioglu; Albert Ali Salah; Theo Gevers edit  doi
openurl 
  Title A Statistical Method for 2D Facial Landmarking Type Journal Article
  Year (up) 2012 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP  
  Volume 21 Issue 2 Pages 844-858  
  Keywords  
  Abstract IF = 3.32
Many facial-analysis approaches rely on robust and accurate automatic facial landmarking to correctly function. In this paper, we describe a statistical method for automatic facial-landmark localization. Our landmarking relies on a parsimonious mixture model of Gabor wavelet features, computed in coarse-to-fine fashion and complemented with a shape prior. We assess the accuracy and the robustness of the proposed approach in extensive cross-database conditions conducted on four face data sets (Face Recognition Grand Challenge, Cohn-Kanade, Bosphorus, and BioID). Our method has 99.33% accuracy on the Bosphorus database and 97.62% accuracy on the BioID database on the average, which improves the state of the art. We show that the method is not significantly affected by low-resolution images, small rotations, facial expressions, and natural occlusions such as beard and mustache. We further test the goodness of the landmarks in a facial expression recognition application and report landmarking-induced improvement over baseline on two separate databases for video-based expression recognition (Cohn-Kanade and BU-4DFE).
 
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  Series Volume Series Issue Edition  
  ISSN 1057-7149 ISBN Medium  
  Area Expedition Conference  
  Notes ALTRES;ISE Approved no  
  Call Number Admin @ si @ DSG 2012 Serial 1853  
Permanent link to this record
 

 
Author Michael Holte; Bhaskar Chakraborty; Jordi Gonzalez; Thomas B. Moeslund edit   pdf
url  doi
openurl 
  Title A Local 3D Motion Descriptor for Multi-View Human Action Recognition from 4D Spatio-Temporal Interest Points Type Journal Article
  Year (up) 2012 Publication IEEE Journal of Selected Topics in Signal Processing Abbreviated Journal J-STSP  
  Volume 6 Issue 5 Pages 553-565  
  Keywords  
  Abstract In this paper, we address the problem of human action recognition in reconstructed 3-D data acquired by multi-camera systems. We contribute to this field by introducing a novel 3-D action recognition approach based on detection of 4-D (3-D space $+$ time) spatio-temporal interest points (STIPs) and local description of 3-D motion features. STIPs are detected in multi-view images and extended to 4-D using 3-D reconstructions of the actors and pixel-to-vertex correspondences of the multi-camera setup. Local 3-D motion descriptors, histogram of optical 3-D flow (HOF3D), are extracted from estimated 3-D optical flow in the neighborhood of each 4-D STIP and made view-invariant. The local HOF3D descriptors are divided using 3-D spatial pyramids to capture and improve the discrimination between arm- and leg-based actions. Based on these pyramids of HOF3D descriptors we build a bag-of-words (BoW) vocabulary of human actions, which is compressed and classified using agglomerative information bottleneck (AIB) and support vector machines (SVMs), respectively. Experiments on the publicly available i3DPost and IXMAS datasets show promising state-of-the-art results and validate the performance and view-invariance of the approach.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1932-4553 ISBN Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number Admin @ si @ HCG2012 Serial 1994  
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Author Wenjuan Gong; Jordi Gonzalez; Xavier Roca edit   pdf
doi  openurl
  Title Human Action Recognition based on Estimated Weak Poses Type Journal Article
  Year (up) 2012 Publication EURASIP Journal on Advances in Signal Processing Abbreviated Journal EURASIPJ  
  Volume Issue Pages  
  Keywords  
  Abstract We present a novel method for human action recognition (HAR) based on estimated poses from image sequences. We use 3D human pose data as additional information and propose a compact human pose representation, called a weak pose, in a low-dimensional space while still keeping the most discriminative information for a given pose. With predicted poses from image features, we map the problem from image feature space to pose space, where a Bag of Poses (BOP) model is learned for the final goal of HAR. The BOP model is a modified version of the classical bag of words pipeline by building the vocabulary based on the most representative weak poses for a given action. Compared with the standard k-means clustering, our vocabulary selection criteria is proven to be more efficient and robust against the inherent challenges of action recognition. Moreover, since for action recognition the ordering of the poses is discriminative, the BOP model incorporates temporal information: in essence, groups of consecutive poses are considered together when computing the vocabulary and assignment. We tested our method on two well-known datasets: HumanEva and IXMAS, to demonstrate that weak poses aid to improve action recognition accuracies. The proposed method is scene-independent and is comparable with the state-of-art method.  
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  Series Editor Series Title Abbreviated Series Title  
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  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number Admin @ si @ GGR2012 Serial 2003  
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Author Noha Elfiky; Jordi Gonzalez; Xavier Roca edit   pdf
doi  openurl
  Title Compact and Adaptive Spatial Pyramids for Scene Recognition Type Journal Article
  Year (up) 2012 Publication Image and Vision Computing Abbreviated Journal IMAVIS  
  Volume 30 Issue 8 Pages 492–500  
  Keywords  
  Abstract Most successful approaches on scenerecognition tend to efficiently combine global image features with spatial local appearance and shape cues. On the other hand, less attention has been devoted for studying spatial texture features within scenes. Our method is based on the insight that scenes can be seen as a composition of micro-texture patterns. This paper analyzes the role of texture along with its spatial layout for scenerecognition. However, one main drawback of the resulting spatial representation is its huge dimensionality. Hence, we propose a technique that addresses this problem by presenting a compactSpatialPyramid (SP) representation. The basis of our compact representation, namely, CompactAdaptiveSpatialPyramid (CASP) consists of a two-stages compression strategy. This strategy is based on the Agglomerative Information Bottleneck (AIB) theory for (i) compressing the least informative SP features, and, (ii) automatically learning the most appropriate shape for each category. Our method exceeds the state-of-the-art results on several challenging scenerecognition data sets.  
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  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number Admin @ si @ EGR2012 Serial 2004  
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Author Jordi Gonzalez; Thomas B. Moeslund; Liang Wang edit   pdf
doi  openurl
  Title Semantic Understanding of Human Behaviors in Image Sequences: From video-surveillance to video-hermeneutics Type Journal Article
  Year (up) 2012 Publication Computer Vision and Image Understanding Abbreviated Journal CVIU  
  Volume 116 Issue 3 Pages 305–306  
  Keywords  
  Abstract Purpose: Atheromatic plaque progression is affected, among others phenomena, by biomechanical, biochemical, and physiological factors. In this paper, the authors introduce a novel framework able to provide both morphological (vessel radius, plaque thickness, and type) and biomechanical (wall shear stress and Von Mises stress) indices of coronary arteries.Methods: First, the approach reconstructs the three-dimensional morphology of the vessel from intravascular ultrasound (IVUS) and Angiographic sequences, requiring minimal user interaction. Then, a computational pipeline allows to automatically assess fluid-dynamic and mechanical indices. Ten coronary arteries are analyzed illustrating the capabilities of the tool and confirming previous technical and clinical observations.Results: The relations between the arterial indices obtained by IVUS measurement and simulations have been quantitatively analyzed along the whole surface of the artery, extending the analysis of the coronary arteries shown in previous state of the art studies. Additionally, for the first time in the literature, the framework allows the computation of the membrane stresses using a simplified mechanical model of the arterial wall.Conclusions: Circumferentially (within a given frame), statistical analysis shows an inverse relation between the wall shear stress and the plaque thickness. At the global level (comparing a frame within the entire vessel), it is observed that heavy plaque accumulations are in general calcified and are located in the areas of the vessel having high wall shear stress. Finally, in their experiments the inverse proportionality between fluid and structural stresses is observed.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1077-3142 ISBN Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number Admin @ si @ GMW2012 Serial 2005  
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