留學生計算機專業dissertation定制：一種三維模型搜索

eNTERFACE’05
July 18- August 12, 2005 – Faculté Polytechnique de Mons, Belgium
A Multimodal (Gesture+Speech) Interface for 3D Model Searchand Retrieval Integrated in a Virtual Assembly ApplicationProject Title: A Multimodal (Gesture+Speech) Interface for 3D Model Search and Retrieval Integrated in a Virtual Assembly Application Principal investigator:
留學生dissertationDr. Dimitrios Tzovaras (ITI-CERTH)
Candidates:Konstantinos Moustakas
Abstract:
The goal of the project is the development of a multimodal interface for content-basedsearch of 3D objects based on sketches. This user interface will integrate graphical,gesture and speech modalities to aid the user in sketching the outline of the 3D objecthe/she wants to search from a large database. Finally, the system will be integrated ina virtual assembly application, where the user will be able to assemble a machinefrom its spare parts using only speech and specific gestures.Project objective:Search and retrieval of 3D objects is a very challenging issue with application
http://www.mythingswp7.com/dissertation_sample/jisuanjiwangluo/branches in numerous areas like recognition in computer vision and mechanicalengineering, content-based search in e-commerce and edutainment applications etc.These application fields will expand in the near future, since the 3D model databasesgrow rapidly due to the improved scanning hardware and modeling software that havebeen recently developed.
The difficulties of expressing multimedia and especially three dimensional content viatext-based descriptors reduces the performance of the text-based search engines toretrieve the desired multimedia content efficiently and effectively. To resolve thisproblem, 3D content-based search and retrieval (S&R) has drawn a lot of attention inthe recent years. A typical S&R system evaluates the similarities between query andtarget objects according to low-level geometric features. However, the requirement ofa query model for searching by example often reduces the applicability of an S&R
platform, since in many cases the user knows what kind of object he wants to retrieve
but he does not have a 3D model to use as query.Imagine the following use case: The user of a virtual assembly application is trying toassemble an engine of its spare parts. He inserts some rigid parts into the virtual sceneand places them in the correct position. At one point he needs to find a piston andassemble it to the engine. In this case, he has to manually search in the database tofind the piston. It would be faster and much more easier if the user had the capabilityof sketching the outline of the piston using specific gestures combined with speech inorder to perform the search.In the context of this project the integration of speech and gestures in the S&Rplatform will be addressed. Speech commands are going to be used for selectingcategories of objects to be searched and for inquiring the automatic sketching ofsimple geometrical objects. The system will also use gesture information for#p#分頁標題#e#
deforming the geometrical shapes, for sketching new lines and curves and also forconnecting them in order to be able to design complex object outlines.
In addition to the research part of the project, it has also an application part since thefinal test bed of the system will be a virtual assembly application.
n particular, the objectives of the project during the workshop will be to research anddevelop fusion strategies and to develop applications in the following areas:
• Gesture and speech recognition
• 3D search and retrieval
• Descriptor extraction using sketches
• Multimodal user interface for 3D S&R
• Speech driven manipulation of the S&R interface
• Prototype implementation of the speech driven 3D S&R platform usingsketches.
• Implementation of the virtual assembly application environment
Detailed technical description:
A. Technical description
This project aims mainly to develop a 3D search and retrieval platform, which willnot use for query a 3D model, but speech and sketches generated from gestures. Theusability of the platform will be tested in a virtual assembly application. It is clear thatthe project is very ambitious for the short period of 4 weeks. However, it is expect tocontribute significantly in the following technical points:
1. 3D S&R platform: Low-level geometrical characteristics of the objects/parts inthe database will be extracted using the spherical trace transform. Variations ofthe method, which will help to the development of the final multimodal S&Rplatform, will be studied.
2. Gesture recognition: Specific gestures will be used to guide the multimodal S&Rplatform. In addition, the system will be able to track the motions of the hands soas to extract the sketches of the objects.
3. Speech recognition: Specific speech commands will guide the S&R interface aswell as the virtual assembly application.
4http://www.mythingswp7.com/dissertation_sample/jisuanjiwangluo/. Integration of gesture & speech: Integration of gesture and speech modalities in
a unified multimodal interface.
5. Definition of “3D sketch descriptors”: The 3D sketches obtained using gesturerecognition and tracking, will be processed so as to create their descriptor, whichwill be used to evaluate the similarity of the sketch with existing 3D models. Thiss the most challenging research part of the project, since there is no direct linkbetween a 3D sketch (i.e. lines in the 3D space) and a 3D virtual object. Specificgestures, which will correspond to deforming, combining, etc, actions areexpected to be useful for the descriptor extraction.
6. Multimodal 3D S&R platform: The 3D S&R platform will be manipulated bythe multimodal (gesture & speech) interface. The following Figure illustrates ablock diagram of the architecture of the platform.Multimodal search and retrieval platform
3D search and retrieval#p#分頁標題#e#
Search and
retrieval module
Descriptor
extraction using
sketches
Gestures
Speech
User interface
Speech
recognition
Gesture
recognition
Action selection
7. Virtual assembly application: The multimodal 3D search and retrieval platform
will be tested in the context of a virtual assembly application. The testing scenario
will be the assembly of a 3D puzzle using sketches.
B. Resources needed
Equipment:
• A personal computer will be needed for each participant.
• At least one of them should be equipped with at least 512 MB of memory and a
GeForce 5700 or higher graphics card.
• Cameras for gesture capturing.
• Microphones for voice recording.
Software:
• Speech recognition software (to be provided by the participators)
• Gesture analysis and recognition software (to be provided by the participators)
Staff:
• Experienced researcher(s) in the area of speech recognition
• Experienced researcher(s) in the area of gesture analysis and recognition
C. Project management
The first task will be to split the participants in three groups:
1. 3D modeling, search and retrieval group
2. Speech recognition group
3. Gesture recognition group
During the workshop these groups will have close cooperation, because their taskswill dependent to each other. At least two times per week meetings will be organizedto discuss in detail the progress of the work and to plan the work of the followingdays.
Workplan and implementation schedule:
Due to the restricted duration of the workshop, preliminary work, i.e. literaturesurvey, team discussions, etc., will be done before the starting date of the workshop.
During the workshop and for each week the following schedule should beapproximately followed.
1st Week:
The first week will be introductory for the participants. Initially, they will be split in 3groups. Next, they will have to set up their computers according to the tasks they willhave to follow during the workshop. The most important tasks during the first week ofthe project are:
• Discussion – exchange of expertise
• System architecture design
• The two last days of the week will be used to implement simple programs in
order to get used to the software, libraries, etc. and to check the feasibility of
the proposed system architecture.
2nd Week:
During the second week each group will work on independent tasks, but all groups
will be in close cooperation due to the interrelation of their tasks. The tasks of each
group during the 2nd week of the project are:
Group 1 (3D modeling, search and retrieval group):
• Development of the S&R graphical interface.
• Development of the multimodal virtual assembly interface
• Development of the sketching system in cooperation with Group 3#p#分頁標題#e#
Group 2 (Speech recognition group):
• Word vocabulary definition
• Development of the speech recognition system.
Group 3 (Gesture recognition group):
• Gesture vocabulary definition
• Development of gesture recognition
• Development of the sketching system in cooperation with Group 1
3rd Week:
The 3rd week will be dedicated to the integration of the developments of each group in
a single platform. Despite the close cooperation of the groups at the 2nd week, during
the integration various problems (e.g. communication, synchronization, etc.) are
expected to arise. The work done in this week will also address these problems by
extending the work of the 2nd week and by designing interfaces for the
communication of the different modalities. In particular, the work will address:
• Integration of the gesture recognition in the 3D S&R system.
• Integration of the speech recognition in the 3D S&R user interface.
• Integration of the developed sketching system to the S&R interface.
• 3D object descriptor extraction using sketches.
• Evaluation of the result – Corrections.
4th Week:
During the 4th week the virtual assembly application will be developed, which will
make use of the multimodal S&R platform implemented during the 3rd week of the
project. Finally, progress, results and evaluation reports will be written and future
work and cooperation will be discussed. Summarizing the work of the 4th week:
• Final implementation of the multimodal virtual assembly application.
• Evaluation – Results – Demonstration
• Progress, evaluation and result reports writing.
• Discussion about future work and cooperation.
Expected outcomes:
At the end of the workshop a multimodal 3D model search and retrieval platform
should have been produced. In addition a virtual assembly application using the
platform should have been implemented. Finally, reports will be also produced
describing in detail the work conducted during the workshop, the methodologies used
and the solution to specific problems that have been arisen.
Profile of team:
A. Leader (with a brief CV)
Dr. Dimitrios Tzovaras
Dr. Dimitrios Tzovaras is a Senior Researcher Grade C (Assistant Professor) at
the Informatics and Telematics Institute. He received the Diploma in Electrical
Engineering and the Ph.D. in 2D and 3D Image Compression from the Aristotle
University of Thessaloniki, Greece in 1992 and 1997, respectively. Prior to his current
position, he was a senior researcher on the Information Processing Laboratory at the
Electrical and Computer Engineering Department of the Aristotle University of
Thessaloniki. His main research interests include virtual reality, haptics, computer#p#分頁標題#e#
graphics, 3D data processing, multimedia image communication, image compression
留學生dissertationand 3D content-based search. His involvement with those research areas has led to the
co-authoring of over thirty articles in refereed journals and more than eighty papers in
international conferences. He has served as a regular reviewer for a number of
international journals and conferences. Since 1992, Dr Tzovaras has been involved in
more than 20 projects, funded by the EC and the Greek Ministry of Research and
Technology. Dr. Tzovaras is an Associate Editor of the Journal on Applied Signal
Processing
B. Staff proposed by the leader (with brief CVs)
Konstantinos Moustakas
Konstantinos Moustakas is a PhD student at the Aristotle University of Thessaloniki,
Greece. He received the Diploma in Electrical and Computer Engineering from the
Aristotle University of Thessaloniki, Greece in 2003. His main research interests
include image and video processing, 3D content based search and retrieval, virtual
reality, computer graphics and computer vision. Currently he is working on rigid and
deformable object modeling and 3D search and retrieval.
C. Other researchers needed (required expertise for each)
In general, researchers with strong background in all areas of the project will be
needed. Priority will be given to:
• Speech recognition: PhD student(s) or researcher(s) with experience in
speech recognition will be needed.
• Gesture recognition: PhD student(s) or researcher(s) with experience in
gesture recognition and/or real-time hand tracking will be needed.
References:
3D content based search and retrieval:
• P.Daras, D.Zarpalas, D.Tzovaras and M.G.Strintzis: "3D Model Search and Retrieval Based on the
Spherical Trace Transform", IEEE International Workshop on Multimedia Signal Processing
(MMSP 2004), Siena, Italy, October 2004.
• D.Zarpalas, P.Daras, D.Tzovaras and M.G.Strintzis: "3D Model Search and Retrieval Based on the
3D Radon Transform", International Conference on Communications (ICC 2004), Multimedia
Technologies and Services Symposium (MMTS), Paris, France, June 2004.
• D.V. Vranic and D. Saupe: “Description of 3d-shape using a complex function on the sphere”. In
Proceedings IEEE International Conference on Multimedia and Expo, pp. 177–180, 2002.
• P.Daras, D.Zarpalas, D.Tzovaras and M.G.Strintzis: "Shape Matching Using the 3D Radon
Transform", 3D Data Processing, Visualization & Transmission (3DPVT 2004), Thessaloniki,
September 2004.
• P.Daras, D.Zarpalas, D.Tzovaras and M.G.Strintzis: "Generalized Radon Transform Based 3D
Feature Extraction for 3D Object C classification", 5th International Workshop on Image Analysis#p#分頁標題#e#
for Multimedia Interactive Services (WIAMIS 2004), Lisboa, Portugal, April 2004.
Speech recognition:
• Kosarev Yu., Ronzhin A., Lee I., Karpov A. “Continuous Speech Recognition without Use of
High-Level Information”, Proceedings of 15-th International Congress of Phonetic Sciences”,
Barcelona, Spain, pp. 1373-1376, 2003.
• Duchnow ki P.,Lum D.S.,Krause J.C.,Sexton M.G.,Bratakos M.S., Braida L.D., “Development of
speechreading supplements based on automatic speech recognition”, IEEE Transactions on
Biomedical Engineering,April 2000,47(4):487-496.
• S. Oviat, P. Cohen, L. Wu, J. Vergo, L Duncan, B. Suhm, J. Bers, T. Holzman, T. Winograd, J.
Landay, J. Larson and D. Ferro “Designing the User Interface for Multimodal Speech and Penbased
Gesture Applications: State-of-the-Art Systems and Future Research Directions”, Human
Computer Interaction, 15(4):263--322, August 2000.
• Rabiner, L. R., and Schafer R. W., Digital Processing of Speech Signals, Prentice Hall, 1978.
• Alexey A. Karpov, Andrey L. Ronzhin, Alexander I. Nechaev, Svetlana E. Chernakova. Assistive
multimodal system based on speech recognition and head tracking, Proc. of the 9-th International
Conference SPECOM’2004, St. Petersburg: “Anatoliya”, 2004, pp. 521-530
• Kosarev Yu., Lee I., Ronzhin A., Karpov A., Savage J., Haritatos F. “Robust Speech
Understanding for Voice control system”. Proceedings of Workshop SPECOM'2002,
St. Petersburg, pp. 13-18, 2002.
Gesture recognition:
• H. Lee and J.H Kim, “An HMM-Based Threshold Model Approach for Gesture Recognition,”
IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 21, no. 10, pp. 961-973, 1999.
• C. Keskin, A.N. Erkan, L. Akarun, Real time hand tracking and 3D gesture recognition for
interactive interfaces using HMM, Proceedings ICANN/ICONIP, Istanbul, 2003.
• A. Caplier, L Bonnaud, S. Malassiotis, M. Strintzis - Comparison of 2D and 3D Analysis For
Automated Cued Speech Gesture Recognition – SPECOM 2004 Proceedings, St Petersburg,
Russia, September 2004, pp. 35-41.
• R. Grzeszcuk, G. Bradski, M. H. Chu, and J. Y. Bouguet, “Stereo based gesture recognition
http://www.mythingswp7.com/dissertation_sample/jisuanjiwangluo/invariant to 3D pose and lighting,” In Proceedings IEEE Conference on Computer Vision and
Pattern Recognition, vol. 1, 826-833, 2000
• V. I. Pavlovic, R. Sharma, and T. S. Huang. "Visual interpretation of hand gestures for humancomputer
interaction: A review" IEEE Trans. Pattern Anal. and Mach. Intell., 19(7): 677-695, July
1997.
• Shimada, N., Y. Shirai, Y. Kuno, and J. Miura, “Hand Gesture Estimation and Model Refinement#p#分頁標題#e#
Using Monocular Camera - Ambiguity Limitation by Inequality Constraints", Proceedings of 3rd
Conference of Face and Gesture recognition, pp. 268-273, 1998.