1. A visual surveillance using real-time curve evolution based on the level-set method and pan-tilt camera
Good afternoon ~ sir. Today I want to talk about a subject of study.
Before starting, I went to the conference last week when I could learn about visual surveillance, that was
So in my survey, the title is A visual ~~~.
I hope that all of you will pay attention to me and cooperate me during my presentation.
Dept. of Visual Contents, Dongseo University
Seung Il Han

2. Method of Real-time curve evolution
Outline
Objective
Method of Real-time curve evolution
Composition of real-time curve evolution
Advanced curve evolution method
The proposed system
Binary process
Active contour
Experiment
Conclusion
REFERENCE
My presentation will go on through there main steps. ~
I will describe each step in detail with help of presentation slides.
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,

3. < Result of subtraction >
Objective
< Pan&Tilt Camera >
< Level Set >
< Proposed >
First of all, we come to the purpose for this work, Why we need this kind of system, how this system can perform better than conventional case.
The reason is that how to use the pan& tilt camera. P&T camera more useful than the normal camera such as CCD or web camera. Because normal camera has the fixed angle. So they are restricted to see the wide area, or some area that is interested. So. They are restricted within narrow limits.
Now pan & tilt camera are used by human being. It’s just available to us. So we propose the automatically surveillance by using some computational technique.
In here I simply talk about what is the Object in image. How to find something image.
As you can see, result of subtraction. White color blob is interested area. We called this blob Object. And black area is not interested area and called background.
It’s the problem, How to detect this blob exactly that human or some stuff has movement.
But pan tilt camera has some problem.
Conventional image processing technique has many kind of methods that is called analysis of color or subtraction of image or edge detection. Patter matching in image.
Digital image was made up RGB, It has just color value. And It could be changed by some equation. His, Ycbcr, of cause they have not only color value
But also illuminance and saturation. But this way have so many noise. It’s difficult to classify similar color and It’s so dependent environment.
Because with the help of this system Any user can interact with machine anytime, anywhere. Actually, the system makes the usage of digital devices more comfortable on public places like airport, railway station, bus station, and hospital etc(ET CETERA).
< Result of subtraction >
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,

4. Image subtraction < Background subtraction >
So we use subtraction image, but It also has problem.
Image subtraction has to use base image. What is the base image.
In this image It’s the base image and conventional image subtraction which compare between there two image.
But, as the case may be, it has noise also. I think it’s needed to eliminate these noise.
Anyway, in my case, could not use base image so I just compare previous frame with current frame.
You can see the blob also but It’s so week that can not use the this information.
So we use the curve evolution method to detect and make up the Object that is robust.
Return to the previous page.
We can remove noise and fill up the blob.
And then we use the curve evolution
< Background subtraction >
< Near frame subtraction > 4
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,

5. 1. Method of Real-time curve evolution
Next, I’m going to explain curve evolution. It’s the active contour algorithm for detecting object.
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,

6. Composition of real-time curve evolution
I want to talk what is the active contour and how to use to image simply.
What is this.
As you can see this figure.
This is conception and function map.
Firs is the F which is the binary map.
You saw the previous page.
And then there is also Phi map.
It has condition that When to move the lines, how to move the lines and which direction move the lines. 6
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,

7. Process of real-time curve evolution
And It’s the flow of the two lines to detect the object contour.
These lines are moved with this flow.
Along the flow, you can see this image.
Two line can detect where is the object. And we can use this area information.
< Advanced curve evolution > 7
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,

8. 2. The Proposed system 8
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,

9. The proposed system < Flow chart >
It meat continuously input of images.
The first step is subtraction image.
< Flow chart > 9
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,

10. The proposed system It’s application to the real-image.
These figure are the continuous image from camera.
And below-left image is result using conventional case which just used subtraction.
Below and right image is propose method result figure.
As you can see, Object is robust as well as center point exactly position. 10
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,

11. < Pan & Tilt control>
When to move the camera
In this slide, I want to describe about the control of camera.
When the center point is out of the this range.
Camera move to object direction.
< Pan & Tilt control> 11
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,

12. 3. Experiment & Conclusion
First of all, I’m going to introduce this Vision Based hand tracking system, 12
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,

13. < The proposed method > < Conventional method >
Experiment
< The proposed method >
In this slide, I want to describe about the configuration of the system developed.
First of all, we need one stereo camera and one display device with computer as hardware part.
Further In software segment we have utilized concepts of image processing,
stereo matching and coordinate mapping.
The specification of hardware used are shown here.
< Conventional method > 13
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,

14. < Continuous frame of proposed case >
Experiment
< Continuous frame of proposed case > 14
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,

15. < Continuous frame of conventional case>
Experiment
In this slide, I want to describe about the configuration of the system developed.
First of all, we need one stereo camera and one display device with computer as hardware part.
Further In software segment we have utilized concepts of image processing,
stereo matching and coordinate mapping.
The specification of hardware used are shown here.
< Continuous frame of conventional case> 15
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,

16. Experiment < Center point in proposed case >
This slide, I would like to show you, How much is proposed case’s tracking performance better than conventional case.
Also, as you can see, left image the line which is sequential movement of the center point.
< Center point in proposed case >
< Center point in conventional case > 16
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,

17. Conclusion This Now I’m going to see you a video of experiment. 17
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,

18. References
[1] Yonggang Shi, William Clem Karl, “A Real-Time Algorithm for the Approximation of Level-Set-Based Curve Evolution”, vol.17, no.5, pp , IEEE transactions on image processing, May 2008.
[2] S.Osher and J.Sethian, “Fronts propagation with curvature dependent speed: Algorithms based on Hamilton-Jacobi formulations” J.Comput. Phys., vol. 79, pp , 1988.
[3] D.Peng, B.Merriman, S.Osher, H.Zhao, M.Kang, “APDE-based fast local level set method,” J. Comput. Phys., vol. 155, pp , 1999.
[4] S.Osher, R.Fedkiw, “Level-Set Methods and Dynamic Implicit Surfaces.” pp , pp , New York: Springer Verlag, 2002.
[5] J.Sethian, “Level-Set Methods and Fast mat-ching Methods: Evolving Interfaces in Computat-ional Geometry, Fluid Mechanics, Computer Vision, and Materials Science.”, Cambridge, U.K.: Cambridge Univ. Press,
Here are the research papers, I have referred for my work.
It all about my presentation, If you have any question, you are welcome to ask. I will try my best to explain.
Thank you very much.
I sorry. I can not describe you here but I can write you definitely. Sorry for that, 18
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,

19. Thank You 19
INSTITUTE OF AMBIENT INTELIGENT, Han Seung Il, Dongseo Univ,