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
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 4418, 636 Seiten, eBook

Reihe: Lecture Notes in Computer Science

This volume contains the papers accepted for presentation atMIRAGE 2007. The Mirage conference is becoming recognized internationally, with pres- tations coming from 31 countries. South Korea proved to be the most active scienti?cally with a total of 73 submitted papers, far aboveChina (27 submitted papers), Taiwan (10) and India (9), which proves the strong domination of Asia in the development of this new technology. We received a total of 198 submissions. Reviewing was very selective as the Program Committee accepted only 42 oral presentations and 17 posters. We had to extend the conference period from two to three days, as the number of submissions was mutiplied by three compared to the previous conference, which proves that this conference attracts more and more researchers. All papers were reviewedby two to four members of the ProgramCommittee. The ?nal selection was carried out by the Conference Chairs. We wish to thank the Program Committee and additional referees for their timely and high-quality reviews.We also thank the invited speakers Peter Eisert and Adrian Hilton for kindly accepting to present very interesting talks. Mirage 2007 was organized by inria Rocquencourt and took place at inria, Rocquencourt, close to Versailles Castle. We believe that the conference proved tobeastimulating experience,andwehopereaderswillenjoytheseproceedings. January 2007 A. Gagalowicz W. Philips Organization Mirage 2007 was organized by inria and Ghent University.

Zielgruppe

Research

Autoren/Hrsg.

Gagalowicz, André

Gagalowicz, Andre

Philips, Wilfried

Inhaltsverzeichnis

Published Papers.- An Improved Color Mood Blending Between Images Via Fuzzy Relationship.- Evaluation of Alzheimer’s Disease by Analysis of MR Images Using Multilayer Perceptrons, Polynomial Nets and Kohonen LVQ Classifiers.- Joint Bayesian PET Reconstruction Algorithm Using a Quadratic Hybrid Multi-order Prior.- Automatic Combination of Feature Descriptors for Effective 3D Shape Retrieval.- Spatio-temporal Reflectance Sharing for Relightable 3D Video.- Interactive Hierarchical Level of Detail Level Selection Algorithm for Point Based Rendering.- Fast Ray-Triangle Intersection Computation Using Reconfigurable Hardware.- An Applicable Hierarchical Clustering Algorithm for Content-Based Image Retrieval.- MADE: A Composite Visual-Based 3D Shape Descriptor.- Research of 3D Chinese Calligraphic Handwriting Recur System and Its Key Algorithm.- Clouds and Atmospheric Phenomena Simulation in Real-Time 3D Graphics.- Feature Points Detection Using Combined Character Along Principal Orientation.- Fast Virtual Cloth Energy Minimization.- Model-Based Feature Extraction for Gait Analysis and Recognition.- Interactive System for Efficient Video Cartooning.- Virtual Reality Technology Used to Develop Didactic Models.- Copying Behaviour of Expressive Motion.- Illumination Compensation Algorithm Using Eigenspaces Transformation for Facial Images.- Reverse Engineering Garments.- 3D Reconstruction of a Human Face from Images Using Morphological Adaptation.- Robust Automatic Data Decomposition Using a Modified Sparse NMF.- A Brain MRI/SPECT Registration System Using an Adaptive Similarity Metric: Application on the Evaluation of Parkinson’s Disease.- Hand Gesture Recognition with a Novel IR Time-of-Flight Range Camera–A Pilot Study.- 3D Reconstruction of Human Faces from OccludingContours.- The Multiresolution Analysis of Triangle Surface Meshes with Lifting Scheme.- A Note on the Discrete Binary Mumford-Shah Model.- Model-Based Plane-Segmentation Using Optical Flow and Dominant Plane.- A Study on Eye Gaze Estimation Method Based on Cornea Model of Human Eye.- Generation of Expression Space for Realtime Facial Expression Control of 3D Avatar.- Improving Efficiency of Density-Based Shape Descriptors for 3D Object Retrieval.- Segmentation of Soft Shadows Based on a Daylight- and Penumbra Model.- Sub-pixel Edge Fitting Using B-Spline.- Re-mapping Animation Parameters Between Multiple Types of Facial Model.- Data-Driven Animation of Crowds.- A 3-D Mesh Sequence Coding Using the Combination of Spatial and Temporal Wavelet Analysis.- Detection of Wilt by Analyzing Color and Stereo Vision Data of Plant.- Human Silhouette Extraction Method Using Region Based Background Subtraction.- Facial Feature Point Extraction Using the Adaptive Mean Shape in Active Shape Model.- Use of Multiple Contexts for Real Time Face Identification.- Computerized Bone Age Assessment Using DCT and LDA.- Natural Image Matting Based on Neighbor Embedding.- Epipolar Geometry Via Rectification of Spherical Images.- Parallel Implementation of Elastic Grid Matching Using Cellular Neural Networks.- Automatic Segmentation of Natural Scene Images Based on Chromatic and Achromatic Components.- 3D Model-Based Tracking of the Human Body in Monocular Gray-Level Images.- Measurement of the Position of the Overhead Electric-Railway Line Using the Stereo Images.- Hand Shape Recognition by Hand Shape Scaling, Weight Magnifying and Finger Geometry Comparison.- Volumetric Bias Correction.- Object Tracking with Particle Filter Using Color Information.- Fitting Subdivision Surface Models to Noisyand Incomplete 3-D Data.- Classification of Facial Expressions Using K-Nearest Neighbor Classifier.- Cortical Bone Classification by Local Context Analysis.- Line Segment Based Watershed Segmentation.- A New Content-Based Image Retrieval Approach Based on Pattern Orientation Histogram.- A Robust Eye Detection Method in Facial Region.- Accuracy Improvement of Lung Cancer Detection Based on Spatial Statistical Analysis of Thoracic CT Scans.

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.