1 / 18

Sketch Characterization and Compression for Nomadic Computing

Explore the problem of handling sketch data in real-time on mobile devices and propose two new algorithms for characterizing and compressing sketches. Evaluate the performance of these algorithms against existing methods and assess the subjective perception of information loss.

carolinegraham
Download Presentation

Sketch Characterization and Compression for Nomadic Computing

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. Sketchs characterization and compression for nomadic computing Nelson Baloian, Ramón Cruzat, Richard Ibarra Departamento de Ciencias de la Computación Universidad de Chile Javier Bustos-Jiménez ORAND

  2. Motivation • Mobile computing: • Learning • Design • Planning • Geology • Topography • Engeneering

  3. Our Experience • Mobile collaborative applications • P2P architechture • Based on sketching & gesturing

  4. The problem • Sketching originates lots of data • Must be shared in real time • Mobile devices have low memory & processig capacity sketch

  5. The solution • Reduce data • How ? • Characterizing and “compressing” sketches • But this is not new ! • Jones, Durand & Desbrun • Lee et al. • Ramer, Douglas,Peucker • They still demad too much computation power • Results are not satisfactory for the mobile scenario

  6. Our proposal: Two new algorithms • Distance-based algorithm. • If distance AB is less than e point B can be discarded • Area-based algorithm. • Areas covered by trapezoid ABCX and ACX are compared to decide if B does provide additional information

  7. Evaluation (1) • Evaluation parameters • Time for characterizing & compressing sketch (t). • Size of resulting characterization (s). • % of information loosing due the compression (l). calculated as ||O − R||/||O||, • O is the pixel matrix of the original image and • R is the pixel matrix of the reconstructed image

  8. Evaluation (2) • Compare against what ? • Algoritms from the literature already discarted • Strightforward algorothms: • Image algorithm take a photo of the sketch and scale it, for reducing the size of the image. • Compression algorithm use the JavaScript Objection Notation (JSON) for representing the data as an array of pairs [[20.7, 10.2], [8.3, 15.4], ...] and zip it

  9. Evaluation tool: X application • Java application for freehand sketching • Transformation algorithms as plug-ins • Generates statistics

  10. Statistics: HTML file

  11. Experiments - 1 • A basic Sketch: rectangle • Processed by 4 algoritms • Area with e = 1, 100, 1000 square pixels • Distance with e = 1, 100 and 1000 pixels • Scaling • Coding and zipping

  12. Experiments - 2 • A basic Sketch: cross • Processed by 4 algoritms • Area with e = 1, 100, 1000 square pixels • Distance with e = 1, 100 and 1000 pixels • Scaling • Coding and zipping

  13. Experiments - 3 • Advanced Sketch: figure • Processedby 4 algoritms • Areawith e = 1, 100, 1000 squarepixels • Distancewith e = 1, 100 and 1000 pixels • Scaling • Coding and zipping

  14. Experiments - 4 • Advanced Sketch: handwriting • Processedby 4 algoritms • Areawith e = 1, 100, 1000 squarepixels • Distancewith e = 1, 100 and 1000 pixels • Scaling • Coding and zipping

  15. Results: mean values basic sketches

  16. Mean values for advanced sketches

  17. Subjective evaluation • How does the human user percieves the lose of information

  18. Conclusions • It does pay off ! • Results are valid for the current state of the art -> with more mobile computing power, other algoritms can be evaluated • A methodology for evaluating how good are compression algorithms • Combined with other mechanisms

More Related