VPF – Video Processing and Filtering, Applied for Surveillance System

The research explores the video processing techniques for visual monitoring, such as, video surveillance, meeting mining, and human activity understanding. The basic techniques of processing video from static cameras, object detection, tracking and recognition, trajectory analysis and object classification. The specific problems, for example, face analysis, license plate recognition, under vehicle scanner, parking system, helmet detector, gesture analysis and recognition, vehical logo/color recognition, leave largage, intrusion, pedestrian detection and etc. More advanced problems using multiple cameras and moving cameras, such as, the 3d localization, fall detection and etc. Privacy issues will also be examined, focusing on how automatic processing can protect privacy?

Image Matching for Motion Analysis and Stereo vision

This research is invested on image matching methods, and their applications. It is divided into two parts: methodological and engineering. The first tackles decision methods used to match features between images. We found it on the “stable marriage” paradigm. Several algorithms are developed with constraints added, as global satisfaction or equity, for better adapting to application needs as controlling a certain local/global balance in the decision. Then, we introduce a generic matching system based on these algorithms where stable marriages become the key mechanism. The second part is devoted to applicative processes building on this matching core. First, level lines and their junctions are selected for primitive features to be paired in all applications. Then, the adapted implementation of the core is studied in the following applications : a registration system, a system for obstacle detection from stereo pairs, and a generic system for otion analysis. The matching quality is experimented on and tested in all three applications. It is compared with vote based and dynamic programming based matching results.

In stereovision, the method is implemented on PiCar platform (embedded electrical car) for obstacle detection. The RT-maps is used for real time analysis.

mvt1 mvt2 mvt3
route1 route3 route2

In the case of motion analysis, we present a general system for motion understanding: features extraction (‘level sets’ to ‘junctions’), features matching (‘flow’ for two associated junctions), motion classification (‘flows’), image segmentation (‘junctions’ to ‘level sets’, object). In that case, some additional algorithms are proposed, like the fuzzy c-mean with spatial constraint on level sets algorithm, snake algorithm for level sets segmentation and etc.

Motion segmentation, test on human motion sequence and car sequence.

eflam The EFLAM is an efficient approach for the detection of level-line junctions in images. Potential junctions are exhibited independent from noise by their consistent local level-variation. Then, level-lines are tracked through junctions in descending the level-line flow. Flow junctions are extracted as image primitives to support matching in many applications.The primitive is robust against contrast changes and noise. It is easily made rotation invariant. As far as the image content allows, the spread of junctions can be controlled for even spatial distribution. We show some results and compare with the Harris detector.

SM – Stable Marriages Matching

The problem statement, if we have N men and M women to be married. How to marry them? in the conditions that, (1) global marriage is stable, (2) everyone is satisfy with her or his partner, and (3) the fairness on their sex need to be respected. This is one of the most popular combinatorial problems that were firstly studied by Gale and Shapley in 1962.

We proposed a familly of algorithms (OZ, BZ, RZ, RGS, S-fasion) based on a novel representation, so-called the marriage table, to solve this problem.

Thesis

N. Suvonvorn, Mise en correspondance d’images pour l’analyse du mouvement et la stéréovision (In french), PhD dissertation, Universit? de Paris XI, Paris, France, 2006.

Journals

N. Suvonvorn and B. Zavidovique, (2009), System for Motion Analysis based on Level Sets, Journal on Image and Vision Computing – Elsevier (IMVIS), Submitted.
N. Suvonvorn and B. Zavidovique, (2009), Globally Satisfying and Equitable Stable Marriages and Their Complexity, International Journal of Pure and Applied Mathematics (IJPAM), 2009, Volume: 53, Issue: 3, page(s): 439-466, ISSN: 1311-8080.

Publications

Teerasak Kroputaponchai and Nikom Suvonvorn, (2009), Vision-based Fall Detection and Alert System Suitable for the Elderly and Disable Peoples, In Proceedings of 24th Japanese Conference on the Advancement of Assistive and Rehabilitation Technology (JCAART), August 26-28, 2009, Tokorozawa, Japan, Accepted.
Sofina Yakhu and Nikom Suvonvorn, (2009), Key Frame Extraction from Video Sequence Using a Face Quality Index Applied to Surveillance System , In Proceedings of ECTI Conference on Application Research and Development (ECTI-CARD), May 4-6, 2009, Thailand, p.409-413. ISBN: 978-974-8285-62-7.
Thanatip Limna, Pichaya Tandayya and Nikom Suvonvorn, (2009), Low-cost Stereo Vision System for Supporting the Visually Impaired’s Walk , In Proceedings of 3rd international Convention on Rehabilitative Engineering & Assistive Technology (i-CREATe), April 22-26, 2009, Singapore.
N. Suvonvorn and A.Chocksuriwong, (2008), Real-time face detection/identification for surveillance system, In Proceedings of IEEE International Conference on Electronic Design (ICED), December 1-3, 2008, Penang, Malaysia, p.1-5. ISBN: 978-1-4244-2315-6.
N. Suvonvorn, F. Le Coat, B. Zavidovique, (2007), Marrying level-line junctions for obstacle detection, In Proceedings of IEEE International Conference on Image Processing (ICIP), September 16-19, 2007, San Antonio, Texas, USA, p.305-308. ISBN: 1-4244-1437-7..
N. Suvonvorn and B. Zavidovique, (2006), EFLAM : A model to level-line junction extraction, In Proceedings of International Conference on Computer Vision Theory and Applications (VISAPP), February 25 – 28, 2006, INSTICC, Setubal, Portugal, p. 257-264.
N. Suvonvorn, S. Bouchafa and B. Zavidovique, (2005), Marrying level lines for stereo or motion, In Proceedings of International Conference on Image Analysis and Recognition (ICIAR), September 28-30, 2005, Toronto, Canada, p. 391-398.
N. Suvonvorn, S. Bouchafa and L. Lacassagne, (2004), Fast Reliable Level-Lines Segments Extraction, In Proceedings of IEEEs International Conference on Information and Communication Technologies: from Theory to Applications (ICTTA), April 19-23, 2004, Damascus, Syria, p. 349- 350.
N. Suvonvorn, 2004, Algorithm for level-lines extraction, In Proceedings of the First Academic Conference of Thai Students in France and Europe, organized by the Association of Thai Students in France under royal patronage of Thailand, June 14, 2004, Montpelier, France.
M. Zavidovique, N. Suvonvorn, (2007), Table-turning to Stable Marriage Satisfaction and Equity, In Proceedings of IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing, September 10-12, 2007, Bucharest, Romania, vol. 1, p. 179-184.
N. Suvonvorn and B. Zavidovique, (2006), A Stable Marriages Algorithm to Optimize Satisfaction and Equity, In Proceedings of International Conference on Image Analysis and Recognition (ICIAR), September 18-20, 2006, Povoa de Varzim, Portugal, vol. 2, pp. 422-433.
B. Zavidovique, N. Suvonvorn and Guna S. Seetharaman, (2005), A Novel representation and algorithms for (quasi) stable marriages, In Proceedings of International Conference on Informatics in Control, Automation and Robotics (ICINCO), September 14-17, 2005, Barcelona, Spain, p. 63-70.
N. Suvonvorn, (2005), Novel algorithms of stable marriages problem,In Proceedings of the First Academic Conference of Thai Students in France and Europe, organized by the Association of Thai Students in France under royal patronage of Thailand, June 14, 2005, Paris, France.