Gagalowicz / Philips Computer Vision/Computer Graphics Collaboration Techniques

Third International Conference on Computer Vision/Computer Graphics, MIRAGE 2007, Rocquencourt, France, March 28-30, 2007, Proceedings
2007
ISBN: 978-3-540-71457-6
Verlag: Springer Berlin Heidelberg
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 636 Seiten

Reihe: Image Processing, Computer Vision, Pattern Recognition, and Graphics

This book constitutes the refereed proceedings of the Third International Conference on Computer Vision/Computer Graphics collaboration techniques involving image analysis/synthesis approaches MIRAGE 2007, held in Rocquencourt, France, in March 2007.

The 55 revised full papers presented were carefully reviewed and selected from 198 submissions. The papers cover foundational and methodological issues such as model-based imaging and analysis, image-based modeling and 3D reconstruction, data driven animation, image and video-based lighting and rendering, model-based vision approaches, model-based indexing and database retrieval, model-based object tracking in image sequences, model-based image and shape analysis, model-based video compression techniques.

Application issues addressed are human/computer interfaces, video-games and entertainment industry, media productions from and for films, broadcasts and games, post-production, computer animation, virtual effects, realistic 3D simulation, virtual prototyping, multimedia applications, multimedia database classification, virtual and augmented reality, medical and biomedical applications.

Written for: Researchers and professionals

Keywords: 3D vision, algorithmic learning, biomedical images, classification, clustering, computer vision, face identification, face reconstruction, gesture recognition, image analysis, image processing, image registration, image retrieval, image segmentation, machine learning, neural networks, object detection, object recognition, object tracking, pattern recognition, ray tracing, segmentation

Autoren/Hrsg.

Gagalowicz, André

Gagalowicz, Andre

Philips, Wilfried

Inhaltsverzeichnis

1;Title page;2
2;Preface;6
3;Organization;8
4;Table of Contents;12
5;An Improved Color Mood Blending Between Images Via Fuzzy Relationship;17
6;Evaluation of Alzheimer’s Disease by Analysis of MR Images Using Multilayer Perceptrons, Polynomial Nets and Kohonen LVQ Classifiers;28
7;Joint Bayesian PET Reconstruction Algorithm Using a Quadratic Hybrid Multi-order Prior;39
8;Automatic Combination of Feature Descriptors for Effective 3D Shape Retrieval;52
9;Spatio-temporal Reflectance Sharing for Relightable 3D Video;63
10;Interactive Hierarchical Level of Detail Level Selection Algorithm for Point Based Rendering;75
11;Fast Ray-Triangle Intersection Computation Using Reconfigurable Hardware;86
12;An Applicable Hierarchical Clustering Algorithm for Content-Based Image Retrieval;98
13;MADE: A Composite Visual-Based 3D Shape Descriptor;109
14;Research of 3D Chinese Calligraphic Handwriting Recur System and Its Key Algorithm;121
15;Clouds and Atmospheric Phenomena Simulation in Real-Time 3D Graphics;133
16;Feature Points Detection Using Combined Character Along Principal Orientation;144
17;Fast Virtual Cloth Energy Minimization;155
18;Model-Based Feature Extraction for Gait Analysis and Recognition;166
19;Interactive System for Efficient Video Cartooning;177
20;Virtual Reality Technology Used to Develop Didactic Models;189
21;Copying Behaviour of Expressive Motion;196
22;Illumination Compensation Algorithm Using Eigenspaces Transformation for Facial Images;208
23;Reverse Engineering Garments;216
24;3D Reconstruction of a Human Face from Images Using Morphological Adaptation;228
25;Robust Automatic Data Decomposition Using a Modified Sparse NMF;241
26;A Brain MRI/SPECT Registration System Using an Adaptive Similarity Metric: Application on the Evaluation of Parkinson’s Disease;251
27;Hand Gesture Recognition with a Novel IR Time-of-Flight Range Camera–A Pilot Study;263
28;3D Reconstruction of Human Faces from Occluding Contours;277
29;The Multiresolution Analysis of Triangle Surface Meshes with Lifting Scheme;290
30;A Note on the Discrete Binary Mumford-Shah Model;299
31;Model-Based Plane-Segmentation Using Optical Flow and Dominant Plane;311
32;A Study on Eye Gaze Estimation Method Based on Cornea Model of Human Eye;323
32.1;Introduction;323
33;Generation of Expression Space for Realtime Facial Expression Control of 3D Avatar;334
34;Improving Efficiency of Density-Based Shape Descriptors for 3D Object Retrieval;346
35;Segmentation of Soft Shadows Based on a Daylight- and Penumbra Model;357
36;Sub-pixel Edge Fitting Using B-Spline;369
37;Re-mapping Animation Parameters Between Multiple Types of Facial Model;381
38;Data-Driven Animation of Crowds;393
39;A 3-D Mesh Sequence Coding Using the Combination of Spatial and Temporal Wavelet Analysis;405
40;Detection of Wilt by Analyzing Color and Stereo Vision Data of Plant;416
41;Human Silhouette Extraction Method Using Region Based Background Subtraction;428
42;Facial Feature Point Extraction Using the Adaptive Mean Shape in Active Shape Model;437
43;Use of Multiple Contexts for Real Time Face Identification;446
44;Computerized Bone Age Assessment Using DCT and LDA;456
45;Natural Image Matting Based on Neighbor Embedding;465
46;Epipolar Geometry Via Rectification of Spherical Images;477
47;Parallel Implementation of Elastic Grid Matching Using Cellular Neural Networks;488
48;Automatic Segmentation of Natural Scene Images Based on Chromatic and Achromatic Components;498
49;3D Model-Based Tracking of the Human Body in Monocular Gray-Level Images;510
50;Measurement of the Position of the Overhead Electric-Railway Line Using the Stereo Images;522
51;Hand Shape Recognition by Hand Shape Scaling, Weight Magnifying and Finger Geometry Comparison;532
52;Volumetric Bias Correction;541
53;Object Tracking with Particle Filter Using Color Information;550
54;Fitting Subdivision Surface Models to Noisy and Incomplete 3-D Data;558
55;Classification of Facial Expressions Using K-Nearest Neighbor Classifier;571
56;Cortical Bone Classification by Local Context Analysis;583
57;Line Segment Based Watershed Segmentation;595
58;A New Content-Based Image Retrieval Approach Based on Pattern Orientation Histogram;603
59;A Robust Eye Detection Method in Facial Region;612
60;Accuracy Improvement of Lung Cancer Detection Based on Spatial Statistical Analysis of Thoracic CT Scans;623
61;Author Index;635

Leseproben

Automatic Combination of Feature Descriptors for E.ective 3D Shape Retrieval (p.49)
Abstract.
We focus on improving the effectiveness of content-based 3D shape retrieval. Motivated by retrieval performance of several individual 3D model feature vectors, we propose a novel method, called prior knowledge based automatic weighted combination, to improve the retrieval effectiveness. The method dynamically determines the weighting scheme for different feature vectors based on the prior knowledge. The experimental results show that the proposed method provides significant improvements on retrieval e.ectiveness of 3D shape search with several measures on a standard 3D database. Compared with two existing combination methods, the prior knowledge weighted combination technique has gained better retrieval effectiveness.

1 Introduction

With the rapid development of 3D scanner technology, graphic hardware, and the World-Wide Web, there has been an explosion in the number of 3D models available on the Internet. In order to make use of these 3D models, the techniques of effective 3D shape retrieval become increasingly significant. 3D models can be annotated by keywords at first, facilitating the text-based retrieval. However, this is not a promising approach, because generally annotations are manually created, which is prohibitively expensive and subject to some factors.

To overcome the disadvantages of annotation-based approach, the so-called contentbased 3D shape retrieval, using the 3D model itself, has been proposed as an alternative mechanism [9]. In [17], Min compared four text annotation-based matching methods and four content-based retrieval approaches, and the experiments showed that the relatively simple solution of using only associated text for retrieval of 3D model was not as effective as using their shape.

As a promising approach applied in many fields, the content-based 3D shape retrieval has attracted many researchers in recent years. In the computer aided design [23], the similar search for standard parts is handy in helping to reach at higher speed with lower cost. In bioinformatics [11], the detection and retrieval of similar protein molecules is applied. Other cases of using this method can be found in the entertainment industry, visual reality, and so forth.

In this paper, we experimentally compare a range of di.erent 3D feature vectors, and the experimental results show that the relative ordering of feature vectors by retrieval effectiveness depends on query models or model classes, which means that no single feature vector can always outperform other feature vectors on all query models. To address the issue and improve the effectiveness of content-based 3D shape retrieval, we propose a novel method, called prior knowledge based automatic weighted combination, which provides significant improvements on retrieval effectiveness of content-based 3D shape search.

Compared with two existing methods, one is using entropy impurity, the other is based on purity-weighted, our method achieves better 3D shape retrieval performance. The rest of this paper is organized as follows. Section 2 introduces the similarity search of 3D objects about feature-based approaches and some feature vectors. Effectiveness measures and retrieval performance for single feature vectors are described in Section 3.