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Three-dimensional point cloud recognition via distributions of geometric distances

Three-dimensional point cloud recognition via distributions ...

引用

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

作者： Mona Mahmoudi Guillermo Sapiro Electrical and Computer Engineering University of Minnesota Minneapolis MN USA

A geometric framework for the recognition of three-dimensional objects represented by point clouds is introduced in this paper. The proposed approach is based on comparing distributions of intrinsic measurements on the point cloud. In particular, intrinsic distances are exploited as signatures for representing the point clouds. The first signature we introduce is the histogram of pairwise diffusion distances between all points on the shape surface. These distances represent the probability of traveling from one point to another in a fixed number of random steps, the average intrinsic distances of all possible paths of a given number of steps between the two points. This signature is augmented by the histogram of the actual pairwise geodesic distances, as well as the distribution of the ratio between these two distances. These signatures are not only geometric but also invariant to bends. We further augment these signatures by the distribution of a curvature function and the distribution of a curvature weighted distance. These histograms are compared using the chi 2 or other common distance metrics for distributions. The presentation of the framework is accompanied by theoretical justification and state-of-the-art experimental results with the standard Princeton 3D shape benchmark and ISDB datasets, as well as a detailed analysis of the particular relevance of each one of the different histogram-based signatures. Finally, we briefly discuss a more local approach where the histograms are computed for a number of overlapping patches from the object rather than the whole shape, thereby opening the door to partial shape comparisons.

关键词： Histograms Shape measurement Geophysics computing Three-dimensional displays Object recognition Level measurement Distributed computing Shape control Digital multimedia broadcasting Data communication

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The cognitive processing mechanism for the players' rule in MMO game

The cognitive processing mechanism for the players' rule in ...

引用

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

作者： Song, Seungkeun Kim, Mijin Song, Doo Heon Division of Digital Contents Dongseo University Korea Republic of Dept. of Computer Game and Information Yong-in Songdam College Korea Republic of

ISBN: (纸本)9780769534961

The goal of this research is to explore the cognitive processing mechanism for players' rule. Based on the protocol analysis on data collected from the player's playing experience in Massively Multi-player Online (MMO) game, we construct a Goal Operator Method Selection Rule (GOMS) model and analyze rule behavior graphs (RBGs) of two different groups of level of expertise in MMO game. In result, we can see the crucial difference between game novices and experts in their behavior patterns. We discuss key implications of this research to support the early stage of game design process and to predict player's playing pattern in the beginning stage of gaming. © 2008 ieee.

关键词： Game design

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Fusion of local appearance with stereo depth for object tracking

Fusion of local appearance with stereo depth for object trac...

引用

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

作者： Feng Tang Michael Harville Hai Tao Ian N. Robinson University of California Santa Cruz Santa Cruz CA US HP Laboratories Palo Alto CA USA University of California Santa Cruz CA USA

Object tracking methods based on stereo cameras, which provide both color and depth data at each pixel, find advantage in separating objects from each other and from background, determining the 3D size and location of objects, and modeling object shape. However, stereo tracking methods to date sometimes fail due to depth image noise, and discard much useful appearance information. We propose augmenting stereo-based models of tracked objects with sparse local appearance features, which have recently been applied with great success to object recognition under pose variation and partial occlusion. Depth data complements sparse local features by informing correct assignment of features to objects, while tracking of stable local appearance features helps overcome distortion of object shape models due to depth noise and partial occlusion. To speed up tracking of many local features, we also use a ldquobinary Gaborrdquo representation that is highly descriptive yet efficiently computed using integral images. In addition, a novel online feature selection and pruning technique is described to focus tracking onto the best localized and most consistent features. A tracking framework fusing all of these aspects is provided, and results for challenging video sequences are discussed.

关键词： Cameras Shape Object recognition Stereo vision Noise shaping Pixel Colored noise Layout Acoustic noise Trajectory

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Distributed segmentation and classification of human actions using a wearable motion sensor network

Distributed segmentation and classification of human actions...

引用

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

作者： A.Y. Yang S. Iyengar S. Sastry R. Bajcsy P. Kuryloski R. Jafari Department of EECS University of California Berkeley USA Department of ECE Cornell University USA Department of EE University of Technology Dallas USA

We propose a distributed recognition method to classify human actions using a low-bandwidth wearable motion sensor network. Given a set of pre-segmented motion sequences as training examples, the algorithm simultaneously segments and classifies human actions, and it also rejects outlying actions that are not in the training set. The classification is distributedly operated on individual sensor nodes and a base station computer. We show that the distribution of multiple action classes satisfies a mixture subspace model, one sub-space for each action class. Given a new test sample, we seek the sparsest linear representation of the sample w.r.t. all training examples. We show that the dominant coefficients in the representation only correspond to the action class of the test sample, and hence its membership is encoded in the representation. We further provide fast linear solvers to compute such representation via l 1 -minimization. Using up to eight body sensors, the algorithm achieves state-of-the-art 98.8% accuracy on a set of 12 action categories. We further demonstrate that the recognition precision only decreases gracefully using smaller subsets of sensors, which validates the robustness of the distributed framework.

关键词： Humans Wearable sensors Sensor systems Base stations Accelerometers Wireless sensor networks computer networks Biomedical monitoring Distributed computing Testing

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Associating audio-visual activity cues in a dominance estimation framework

Associating audio-visual activity cues in a dominance estima...

引用

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

作者： Hayley Hung Yan Huang Chuohao Yeo Daniel Gatica-Perez Idiap Research Institute Martigny Switzerland University of California Berkeley USA International Computer Science Institute Berkeley USA Ecole Polytechnique Federale de Lausanne Switzerland

We address the problem of both estimating the dominant person in a meeting from a single audio source and identifying them visually in a multi-camera setting. We use a speaker diarization algorithm to perform speaker segmentation and clustering, representing when they spoke. Using a greedy ordered audio-visual association algorithm, we investigate using the speaker clusters to find the corresponding person in one of the video channels. The difficulty of the problem is that firstly the speaker diarization output is noisy (e.g. for participants who speak little) and often produces an unequal number of clusters to true participants. Secondly, personal visual activity from natural upper torso motion, which can include highly deformable pose changes and perspective distortion, is computed through computationally efficient coarse features. Our results using almost 2 hours of audio-visual data from 4-participant meetings show a strong correlation between the estimated speaker diarization and visual activity features, enabling the identification of the most dominant person as a pair of audiovisual channels.

关键词： Clustering algorithms Cameras Psychology Feature extraction Signal to noise ratio computer science Torso Bayesian methods Support vector machines Mouth

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Revisiting overlap invariance in medical image alignment

Revisiting overlap invariance in medical image alignment

引用

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

作者： Nathan D. Cahill Julia A. Schnabel J. Alison Noble David J. Hawkes Wolfson Medical Vision Laboratory University of Oxford Oxford UK Research & Innovation Carestream Health Inc. Rochester NY USA Centre for Medical Image Computing University College London London UK

In Studholme et al. introduced normalized mutual information (NMI) as an overlap invariant generalization of mutual information (MI). Even though Studholme showed how NMI could be used effectively in multimodal medical image alignment, the overlap invariance was only established empirically on a few simple examples. In this paper, we illustrate a simple example in which NMI fails to be invariant to changes in overlap size, as do other standard similarity measures including MI, cross correlation (CCorr), correlation coefficient (CCoeff), correlation ratio (CR), and entropy correlation coefficient (ECC). We then derive modified forms of all of these similarity measures that are proven to be invariant to changes in overlap size. This is done by making certain assumptions about background statistics. Experiments on multimodal rigid registration of brain images show that 1) most of the modified similarity measures outperform their standard forms, and 2) the modified version of MI exhibits superior performance over any of the other similarity measures for both CT/MR and PET/MR registration.

关键词： Biomedical imaging Mutual information Measurement standards Size measurement Chromium Entropy Statistics Brain Computed tomography Positron emission tomography

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Research on the Web information system development platform based on MVC design pattern

Research on the Web information system development platform ...

引用

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

作者： Ning, Wang Liming, Li Yanzhang, Wang Yi-Bing, Wang Jing, Wang Management School Dalian University of Technology Dalian Liaoning Province China

ISBN: (纸本)9780769534961

In order to make the Web information system development more efficient, improving the reusability, stability and scalability of system, features of a Web information system development are studied. A Web information system development platform adapting to operational requests and achieving quick development based on MVC design pattern is constructed. After introducing the platform's framework system, the design and realization of its main parts, design philosophy and basic framework of the platform are given, integrating application examples. © 2008 ieee.

关键词： Reusability

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A kidney segmentation approach from DCE-MRI using level sets

A kidney segmentation approach from DCE-MRI using level sets

引用

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

作者： H. Abdelmunim Aly A. Farag W. Miller Mohamed AboelGhar Department of Computer Science Computational Biomedicine Laboratory University of Houston Houston TX USA Computer Vision and Image Processing LabDepartment of Electrical and Computer Engineering University of Louisville Louisville KY USA Medical School Mansoura University Mansoura Egypt

Acute rejection is the most common reason of graft failure after kidney transplantation, and early detection is crucial to survive the transplanted kidney function. Automatic classification of normal and acute rejection transplants from dynamic contrast enhanced magnetic resonance imaging (DCEMRI), is of great importance. Kidney segmentation is the first step for such classification. The image intensity inside the kidney is used as an indication of failure/success. Differentiating between different cases cases is implemented by comparing subsequential kidney scans signals. So, this process is mainly dependent on segmentation. This paper introduces a new shape-based segmentation approach based on level sets. Training shapes are collected from different real data sets to represent the shape variations. Signed distance functions are used to represent these shapes. The methodology incorporates image and shape prior information in a variational framework. The shape registration is considered the backbone of the approach where more general transformations can be used to handle the process. We introduce a novel shape dissimilarity measure that enables the use of different (inhomogeneous) scales. The approach gives successful results compared with other techniques restricted to transformations with homogeneous scales. Results for segmenting kidney images will be illustrated and compared with other approaches to show the efficiency of the proposed technique.

关键词： Level set Image segmentation computer vision Magnetic resonance imaging Shape measurement Biopsy Biomedical computing computer science Image processing Biomedical imaging

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Tracking multiple pedestrians in real-time using kinematics

Tracking multiple pedestrians in real-time using kinematics

引用

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

作者： S. Apewokin B. Valentine R. Bales L. Wills S. Wills School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

We present an algorithm for real-time tracking of multiple pedestrians in a dynamic scene. The algorithm is targeted for embedded systems and reduces computational and storage costs by using an inexpensive kinematic tracking model with only fixed-point arithmetic representations. Our algorithm leverages from the observation that pedestrians in a dynamic scene tend to move with uniform speed over a small number of consecutive frames. We use a multimodal background modeling technique to accurately segment the foreground (moving people) from the background. We then use connectivity analysis to identify blobs in the foreground and calculate the center of mass of each blob. Finally, we establish correspondence between the center of mass of each blob in the current frame with center of mass information gathered from the two immediately preceding frames. We evaluate our algorithm on a real outdoor video sequence taken with an inexpensive webcam. Our implementation successfully tracks each pedestrian from frame to frame in real-time. Our algorithm performs well in challenging situations resulting from occlusion and crowded conditions, running on an eBox-2300 Thin Client VESA PC.

关键词： Kinematics Layout Target tracking Shape Embedded computing Cameras Humans Acceleration Embedded system Computational efficiency

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The randomized approximating graph algorithm for image annotation refinement problem

The randomized approximating graph algorithm for image annot...

引用

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

作者： Yohan Jin Kibum Jin Latifur Khan B. Prabhakaran Multimedia Systems Laboratory University of Texas Dallas Richardson TX USA Data Mining Laboratory University of Texas Dallas Richardson TX USA Computer Institute Dongjak Gu Soongsil University Seoul South Korea

Recently, images on the Web and personal computers are prevalent around the humanpsilas life. To retrieve effectively those images, there are many AIA (Automatic Image Annotation) algorithms. However, it still suffers from low-level accuracy since it couldnpsilat overcome the semantic-gap be tween low-level features (dasiacolorpsila,dasiatexturepsila and dasiashapepsila) and high-level semantic meanings (e.g., dasiaskypsila,dasiabeachpsila). Namely, AIA techniques annotates images with many noisy key words. Refinement process has been appeared in these days and it tries to remove noisy keywords by using Knowledge-base and boosting candidate keywords. Because of limitless of candidate keywords and the incorrectness of web-image textual descriptions, this is the time we need to have deterministic polynomial time algorithm. We show that finding optimal solution for removing noisy keywords in the graph is NP-Complete problem and propose new methodology for KBIAR (Knowledge Based Image Annotation Refinement) using the randomized approximation graph algorithm as the general deterministic polynomial time algorithm.

关键词： Noise shaping Approximation algorithms Polynomials Multimedia systems Image retrieval Shape Humans Buildings Data mining Microcomputers

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