Computational and Biological Vision Course, Semester A, 2006 2.3.06

1. Computational and Biological Vision Course, Semester A, 20062.3.06 Rinat Gotsulsky, 040371163 Roni Rabi, 037668118 Rinat & Roni Segment Painter

2. Our Goal:Segmentation Painter Tool Rinat & Roni Segment Painter

3. Background Rinat & Roni Segment Painter

4. Perceptual Organization • The ability of people to perceive structure in images exists apart from both the perception of 3D and from the recognition of familiar objects. • The action of organize the data even when we have no idea about the picture meaning is important to the Computational Vision and can help to analyze models (known & unknown) • We focus on Segmentation- one of its issues. Rinat & Roni Segment Painter

5. Segmentation • The approach is to divide a single picture into components, objects, text, shading, colors etc. • We are trying to imitate the evolution solution to this approach. • Splitting an image into segments can be an extremely hard problem. • There are no unique definition and one picture can be explicit in billions ways. Rinat & Roni Segment Painter

6. Example: Rinat & Roni Segment Painter

7. Where do we enter the picture? Rinat & Roni Segment Painter

8. SegmentPainter Tool • We developed a toolkit enable people to separate picture to segments. • It enable us to learn about this process and later to apply this approach in computers systems. Rinat & Roni Segment Painter

9. The SegmentPainter Tool Rinat & Roni Segment Painter

10. The SegmentPainter Tool Rinat & Roni Segment Painter

11. SegmentPainter Tool- technical details • The project is cross platform- written in Java language • More then 3000 code line • Support the following actions: File new, open, save, save as, close and exit. • Support in 4 recent files. • Support BMP, JPG, GIF and JPEG images • Support painting lines, curves and free hands (mouse motion) • Support 12 different colors Rinat & Roni Segment Painter

12. Ashort experiment on how people interrupt pictures • Population: 3 groups of people: • Students who take this course. • Students who didn’t take and studding CS. • Other student (from other department). • Experiment: 6 people paint their segments interpretation of 3 pictures. Rinat & Roni Segment Painter

13. Results Rinat & Roni Segment Painter

14. 2 Cs students that take vision course 2 Cs students with on vision course 2 Cs students out “Teva” department Rinat & Roni Segment Painter

15. 2 Cs students that take vision course 2 Cs students with on vision course 2 Cs students out “Teva” department Rinat & Roni Segment Painter

16. 2 Cs students that take vision course 2 Cs students with on vision course 2 Cs students out “Teva” department Rinat & Roni Segment Painter

17. Conclusions Rinat & Roni Segment Painter

18. Segmentation : • In our small research there is no one explanation for a paint. • The segmentation was similar in all of the groups and maybe its from the fact that we see and investigate picture all the time and not because experience and learning of computational vision. • Its not obvious to segment picture – its not a well done algorithm. Rinat & Roni Segment Painter

19. Program SegmentPainter : • There are few must features that need to be added to our toolkit. • The mousses in computers lab must be replaced to better ones (optics). • Segmentation is very difficult to draw. • The Segmentation take a long time. • Need a good qualificationsin painting to draw a segment picture. Rinat & Roni Segment Painter

20. Thanks for interesting course Rinat & Roni Segment Painter