1 / 25

Stylization and Abstraction of Photographs

This paper presents a method for stylizing and abstracting photographs to clarify meaningful information without requiring artistic ability. It utilizes eye movements and visual perception to detect important areas and render the image accordingly.

dendo
Download Presentation

Stylization and Abstraction of Photographs

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Stylization and Abstraction of Photographs Doug Decarlo and Anthony Santella

  2. Outline • Introduction • Goals / Motivation • Image Structure and Analysis • Hierarchical Image Representation • Results • Video Summary • Conclusion

  3. Introduction • The human visual system is very powerful • It masks the complex perceptual and cognitive processing that is needed to understand images • Good information design makes it easer for us to understand images • Keep detail light in unimportant regions • Have fine detail only in important areas

  4. Example • Invert these heuristics and…

  5. Goals • Paper goal: Present a method for stylizing and abstracting photographs to clarify the meaningful information in them with no artistic ability required

  6. Motivation and Contributions • Artists have known about abstraction for years Henri de Toulouse-Lautrec Moulin Rouge-La Goulue

  7. Motivation and Contributions (Cont) • Many different heuristics have been created for emphasizing certain parts of images • But it is very hard to automatically detect meaningful elements in a photograph • Paper’s solution: Use eye movements to help detect the important areas of a photograph

  8. Algorithm Summary • To transform an image: • Instruct a user to look at the image for a short time, obtaining a record of eye movements. • Disassemble the image into its constituents of visual form using visual analysis (image segmentation and edge detection) • Render the image, preserving the form predicted to be meaningful by applying a model of human visual perception to the eye-movement data

  9. Image Structure and Analysis • Edge Detection: The process of extracting out location of high contrast in an image that are likely to form the boundary of objects

  10. Image Structure and Analysis • Image Segmentation: Partitioning an image into contiguous regions of pixels that have similar appearance.

  11. Image Structure and Analysis • For image segmentation, colors were represented in L*u*v space, to produce region boundaries that were more meaningful for human observers

  12. Image Structure and Analysis • Scale-space Theory: Provides a description of images in terms of how content across different resolutions is related • This theory serves as the basis for their hierarchical representation of the image • It uses segmentation algorithms applied at a variety of scales, and finds containment relationships between their results

  13. Visual Perception • Eye movements give a strong indication of the important elements in an image • People can examine only a small area of an image at a time, and therefore scan them in a series of “fixations”

  14. Eye tracker • Use an eye tracking device to figure out the important areas of a photograph

  15. Hierarchical Image Representation • Create an image pyramid of the input image • The bottom image is the original image • Each layer up is a down-sampled by a constant factor • A segmentation algorithm is computed at each later • Edges are detected using the original image, a process called Edge Tracking is used to smooth them

  16. Building the Hierarchy • Construct a tree, a leaf is created for each segmentation in the tree’s bottom image

  17. Rendering with a Perceptual Model • To create the line drawings, the hierarchal tree that was created is “pruned” of leaf nodes in areas where it is determined the user didn’t see • Pruning is done based on the fixations that were recorded and perceptual cues such contrast sensitivity

  18. Region Smoothing • The detail level of boundaries is uniformly high, since all boundaries derive from the lowest segmentation

  19. Drawing Lines • After the segments have been drawn, we draw the lines • When drawing the lines, we ignore lines that were not important (using factors like how close they were to a fixation, how long they are, etc)

  20. Results

  21. Results

  22. Video • Video time…

  23. Future Work • Have the segmenter use a model of shading • Find new ways to represent textures

  24. Conclusion • This paper presented a new visual style using bold edges and constant color and a method of interaction using eye tracking that helps find important areas of a photograph for image rendering

  25. Questions? • ???

More Related