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Modelling user behaviour for Web recommendation using LDA model

Modelling user behaviour for Web recommendation using LDA mo...

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2008 ieee/WIC/ACM International conference on Web Intelligence and Intelligent Agent Technology - workshops, WI-IAT workshops 2008

作者： Xu, Guandong Zhang, Yanchun Yi, Xun School of Computer Science and Mathematics Victoria University PO Box 14428 VIC 8001 Australia

ISBN: (纸本)9780769534961

Web users exhibit a variety of navigational interests through clicking a sequence of Web pages. Analysis of Web usage data will lead to discover Web user access pattern and facilitate users locate more preferable Web pages via collaborative recommending technique. Meanwhile, latent semantic analysis techniques provide a powerful means to capture user access pattern and associated task space. In this paper, we propose a collaborative Web recommendation framework, which employs Latent Dirichlet Allocation (LDA) to model underlying topic-simplex space and discover the associations between user sessions and multiple topics via probability inference. Experiments conducted on real Website usage dataset show that this approach can achieve better recommendation accuracy in comparison to existing techniques. The discovered topic-simplex expression can also provide a better interpretation of user navigational preference. © 2008 ieee.

关键词： Websites

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Estimating 3D facial pose in video with just three points

Estimating 3D facial pose in video with just three points

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Gines Garcia-Mateos Alberto Ruiz Pedro E. Lopez-de-Teruel Antonio L. Rodriguez Lorenzo Fernandez Department Informatica y Sistemas University of Murcia Murcia Spain Department Ingenieria y Tecnologia de Computadores University of Murcia Murcia Spain

Estimating facial pose along a video sequence is an important problem in many applications such as perceptual user interfaces, people monitoring, and aid for the disabled. Currently, most existing methods to compute facial pose are designed to obtain high accuracy under controlled conditions. However, efficiency and robustness are preferable in most practical situations. In this paper, we deal with the problem of 3D pose estimation with the aim to design a fast and approximate solution that requires a minimum amount of information: our method is able to work with just the location of three points -the eyes and the mouth- in each frame. Using that information, and introducing several as sumptions - that could hold in many cases-, we show how to estimate the six degrees of freedom of facial position and orientation. Moreover, one single point could be enough after initializing the system. The obtained accuracy greatly depends on the precision of the underlying 2D face tracker. The system is generic and does not require to be trained for each new user.

关键词： Face detection Humans Eyes Head User interfaces Robustness Mouth computer interfaces Video sequences Skull

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3D face econstruction from a single 2D face image

3D face econstruction from a single 2D face image

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Sung Won Park Jingu Heo Marios Savvides Electrical and Computer Engineering Department Carnegie Mellon University Pittsburgh PA USA

T3D face reconstruction from a single 2D image is mathematically ill-posed. However, to solve ill-posed problems in the area of computer vision, a variety of methods has been proposed; some of the solutions are to estimate latent information or to apply model based approaches. In this paper, we propose a novel method to reconstruct a 3D face from a single 2D face image based on pose estimation and a deformable model of 3D face shape. For 3D face reconstruction from a single 2D face image, it is the first task to estimate the depth lost by 2D projection of 3D faces. Applying the EM algorithm to facial landmarks in a 2D image, we propose a pose estimation algorithm to infer the pose parameters of rotation, scaling, and translation. After estimating the pose, much denser points are interpolated between the landmark points by a 3D deformable model and barycentric coordinates. As opposed to previous literature, our method can locate facial feature points automatically in a 2D facial image. Moreover, we also show that the proposed method for pose estimation can be successfully applied to 3D face reconstruction. Experiments demonstrate that our approach can produce reliable results for reconstructing photorealistic 3D faces.

关键词： Face detection Image reconstruction computer vision Deformable models Parameter estimation Shape Facial features Probability Detectors Interference

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Research on automatic acquiring of Chinese synonyms from Wiki repository

Research on automatic acquiring of Chinese synonyms from Wik...

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2008 ieee/WIC/ACM International conference on Web Intelligence and Intelligent Agent Technology - workshops, WI-IAT workshops 2008

作者： Yong, Lu Hanqing, Hou Nanjing University of Information Science and Technology Nanjing 210044 China College of Information Science and Technology Nanjing Agricultural University Nanjing 210095 China

ISBN: (纸本)9780769534961

Automatic acquiring of synonyms plays an important role in information retrieval and semantic resource development. In order to enhance the ability of the Chinese synonyms acquiring, this paper presents pattern matching approach and PageRank algorithm approach based on the Wiki repository. In pattern matching approach, we analyze the defining and explaining paragraph of the entry in the Wiki repository and form some acquiring rules of synonyms by hands, then automatic extract synonyms by pattern matching. The second method is PageRank algorithm, we analyze the relation between given words and the other words, then construct the associated word graph., and finally use the PageRank algorithm to calculate the similarity degree and discover the synonyms in the associated word graph. The test result indicated that the method is feasible and practical. © 2008 ieee.

关键词： pattern matching

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Investigating how and when perceptual organization cues improve boundary detection in natural images

Investigating how and when perceptual organization cues impr...

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Leandro A. Loss George Bebis Mircea Nicolescu Alexei Skurikhin Computer Vision Laboratory University of Nevada Reno USA Space and Remote Sensing Sciences Los Alamos National Laboratory USA

Boundary detection in natural images represents an important but also challenging problem in computer vision. Motivated by studies in psychophysics claiming that humans use multiple cues for segmentation, several promising methods have been proposed which perform boundary detection by optimally combining local image measurements such as color, texture, and brightness. Very interesting results have been reported by applying these methods on challenging datasets such as the Berkeley segmentation benchmark. Although combining different cues for boundary detection has been shown to outperform methods using a single cue, results can be further improved by integrating perceptual organization cues with the boundary detection process. The main goal of this study is to investigate how and when perceptual organization cues improve boundary detection in natural images. In this context, we investigate the idea of integrating with segmentation the iterative multi-scale tensor voting (IMSTV), a variant of tensor voting (TV) that performs perceptual grouping by analyzing information at multiple-scales and removing background clutter in an iterative fashion, preserving salient, organized structures. The key idea is to use IMSTV to post-process the boundary posterior probability (PB) map produced by segmentation algorithms. Detailed analysis of our experimental results reveals how and when perceptual organization cues are likely to improve or degrade boundary detection. In particular, we show that using perceptual grouping as a post-processing step improves boundary detection in 84% of the grayscale test images in the Berkeley segmentation dataset.

关键词： Image segmentation Tensile stress Voting computer vision Psychology Humans Performance evaluation Brightness TV Information analysis

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Learning-based deformation estimation for fast non-rigid registration

Learning-based deformation estimation for fast non-rigid reg...

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Min-Jeong Kim Myoung-Hee Kim Dinggang Shen Department of Computer Science and Engineering Ewha Womans University Seoul South Korea Department of Radiology and Biomedical Research Imaging Center North Carolina State University Chapel Hill NC USA

This paper presents a learning-based deformation estimation method for fast non-rigid registration. First, a PCA-based statistical deformation model is constructed using the deformation fields obtained by conventional registration algorithms between a template image and training subject images. Then, the constructed statistical model is used to generate a large number of sample deformation fields by resampling in the PCA space. In the meanwhile, by warping the template using these sample deformation fields, the respective sample images in the PCA space can be also generated. Finally, after learning the correlation between the features of the sample images and their deformation coefficients, given a new test image, we can immediately estimate its relative deformations to the template based on its image information. Using this estimated deformation, we can warp the template to generate an intermediate template close to the test image. Since the intermediate template is more similar to the test image compared to the original template, the deformable registration via the intermediate template becomes much easier and faster. Experimental results show that the proposed learning-based registration method can fast register MR brain image with robust performance.

关键词： Shape Deformable models Testing Principal component analysis Brain Image registration Biomedical imaging computer science Biomedical engineering Radiology

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Multivariate analysis of thalamo-cortical connectivity loss in TBI

Multivariate analysis of thalamo-cortical connectivity loss ...

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Jeffrey Duda Brian Avants Junghoon Kim Hui Zhang Sunil Patel John Whyte James Gee Penn Image Computing and Science Laboratory University of Pennsylvania USA Junghoon Kim Albert Einstein Healthcare Network Moss Rehabilitation Research Institute USA

Diffusion tensor (DT) images quantify connectivity patterns in the brain while the T1 modality provides high-resolution images of tissue interfaces. Our objective is to use both modalities to build subject-specific, quantitative models of fiber connections in order to discover effects specific to a neural system. The health of this thalamo-cortical network is compromised by traumatic brain injury, and we hypothesize that these effects are due to a primary injury to the thalamus which results in subsequent compromise of radiating fibers. We first use a population-specific average T1 and DT template to label the thalamus and Brodmann areas (BA) 9,10 and 11 in each subject. We also build an expected connection model within this template space that is transferred to subject space in order to provide a prior restriction on probabilistic tracking performed in subject space. We evaluate the effect of traumatic brain injury on this prefrontal-thalamus network by quantifying, in 10 subjects and 8 controls, the mean diffusion and fractional anisotropy along fiber tracts, along with the mean diffusion within the thalamus and cortical regions. We contrast results gained by a template-based tract definition with those gained by performing analysis in the subject space. Both approaches reveal connectivity effects of TBI, specifically a region of reduced FA in the white matter connecting the thalamus to BA 10.

关键词： Brain modeling Brain injuries Diffusion tensor imaging Anisotropic magnetoresistance Performance analysis Image analysis pattern analysis Brain computer interfaces computer interfaces computer networks

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Exploiting local and global scene constraints in modeling large-scale dynamic 3D scenes from aerial video

Exploiting local and global scene constraints in modeling la...

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Hao Tang Zhigang Zhu Department of Computer Science CUNY Graduate Center New York NY USA Department of Computer Science City College of New York New York NY USA

This paper presents a framework to analyze a large amount of video data and extract high-level structural information - planar structures and motion information - in typical urban scenes, which may be used in video coding or object recognition. The method consists of two phases. In the first phase, multiple parallel-perspective (pushbroom) mosaics are generated from the video data. In the second phase, the planar structures and the moving objects are extracted from the mosaics by a segmentation-based stereo match method. The focus of this paper is the use of local and global scene constraints to improve the accuracy of high-level structural information extraction. The 3D planar patches obtained from the first step of 3D reconstruction are automatically clustered into one or more dominant planes, which are typical in indoor or outdoor city scene and are used to improve the 3D model. Then a local scene constraint is used to further refine the structure of a patch from the structures of its neighboring patches that have better structure estimations. Further, the dominant planes also provide information of road network directions, which greatly facilitates the search of moving objects on the roads. We demonstrate the effectiveness of our approach by experiments on a real video data set of a New York City scene.

关键词： Layout Large-scale systems Cities and towns Cameras Video sequences Data mining computer science Image reconstruction Buildings Roads

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Super-resolution texturing for online virtual globes

Super-resolution texturing for online virtual globes

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Diego Rother Lance Williams Guillermo Sapiro University of Minnesota USA Google Inc. USA

Online virtual globe applications such as Google Earth and Maps, Microsoft Virtual Earth, and Yahoo! Maps, allow users to explore realistic models of the Earth. To provide the ground-level detail of interest to users, it is necessary to serve and render high resolution images. For planetary coverage at high resolution, a very large number of images need to be acquired, stored, and transmitted, with consequent high costs and difficulty for the application provider, often resulting in lower than expected performance. In this work we propose a supplementary approach to render appropriate visual information in these applications. Using super-resolution techniques based on the combination and extension of known texture transfer and synthesis algorithms, we develop a system to efficiently synthesize fine detail consistent with the textures served. This approach dramatically reduces the operational cost of virtual globe displays, which are among the most image-intensive applications on the Internet, while at the same time improving their appearance. The proposed framework is fast and preserves the coherence between corresponding images at different resolutions, allowing consistent and responsive interactive zooming and panning operations. The framework is capable of adapting a library of multiscale textures to pre-segmented regions in the highest-resolution texture maps available. We also describe a simple interface to obtain class label information from contributing users. The presentation of the constituent techniques is complemented with examples simulating our framework embedded in Google Earth.

关键词： Earth Image resolution Displays Rendering (computer graphics) Costs Navigation Pixel Internet Crops Image storage

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3D non-rigid registration for MPU implicit surfaces

3D non-rigid registration for MPU implicit surfaces

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Tung-Ying Lee Shang-Hong Lai Department of Computer Science National Tsing Hua University Hsinchu Taiwan

Implicit surface representation is well suited for surface reconstruction from a large amount of 3D noisy data points with non-uniform sampling density. Previous 3D non-rigid model registration methods can only be applied to the mesh or volume representations, but not directly to implicit surfaces. To our best knowledge, the previous 3D registration methods for implicit surfaces can only handle rigid transformation and they must keep the data points on the surface. In this paper, we propose a new 3D non-rigid registration algorithm to register two multi-level partition of unity (MPU) implicit surfaces with a variational formulation. The 3D non-rigid transformation between two implicit surfaces is a continuous deformation function, which is determined via an energy minimization procedure. Under the octree structure in the MPU surface, each leaf cell is transformed by an individual affine transformation associated with an energy that is related to the distance between two general quadrics. The proposed algorithm can directly register between two 3D implicit surfaces without sampling on the two signed distance functions or polygonalizing implicit surfaces, which makes our algorithm efficient in both computation and memory requirement. Experimental results on 3D human organ and sculpture models demonstrate the effectiveness of the proposed algorithm.

关键词： Surface reconstruction Sampling methods Partitioning algorithms Registers Humans

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