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Detection of comic characters in comic books 
and manga 
17/10/14 - christophe-rigaud.com
2 
17/10/14 - christophe-rigaud.com 
Presentation 
Advisers 
● Jean-Christophe Burie & Jean-Marc Ogier (L3i, La Rochelle, ...
3 
What researchers can do for the paper to digital transition? 
Researchers 
Paper world 
Digital world Digital world 
17...
4 
Researchers 
Image credits: contributors of the eBDtheque dataset 
17/10/14 - christophe-rigaud.com
5 
17/10/14 - christophe-rigaud.com 
Balloon classification 
Speaker localization 
Text timestamps 
Tone and pitch 
Scene ...
6 
17/10/14 - christophe-rigaud.com 
Balloon classification 
Speaker localization 
Text timestamps 
Tone and pitch 
Scene ...
7 
17/10/14 - christophe-rigaud.com 
Balloon classification 
Speaker localization 
Text timestamps 
Tone and pitch 
Scene ...
8 
CCHHAARRAACCTTEERRSS 
17/10/14 - christophe-rigaud.com 
Balloon classification 
Speaker localization 
Text timestamps 
...
9 
Challenges of comics analysis 
● Variation of comic book styles 
● Printing & scanning method changes over time (press,...
11 
Summary of comic character extraction 
17/10/14 - christophe-rigaud.com 
● Supervised approaches 
● Character spotting...
12 
Summary of comic character extraction 
17/10/14 - christophe-rigaud.com 
● Supervised approaches 
● Character spotting...
13 
Character spotting given an example [5] 
● Aim: retrieve all the instances (apparitions) of a given character in all t...
14 
1) Color reduction/quantization 
N>10000 N=256 N=32 
17/10/14 - christophe-rigaud.com
15 
17/10/14 - christophe-rigaud.com 
2) User query
16 
3) Color selection: occurrence level 
17/10/14 - christophe-rigaud.com
17 
3) Color selection: occurrence + discriminality levels 
17/10/14 - christophe-rigaud.com 
Top 3 colors
18 
4) Character spotting: example 
17/10/14 - christophe-rigaud.com 
User input 
Image credits: (Prunelle, la fille du cy...
19 
4) Character spotting: example 
correct detections wrong detections 
17/10/14 - christophe-rigaud.com
20 
17/10/14 - christophe-rigaud.com 
Conclusions 
● Contributions 
● Content Based Drawing Retrieval 
● Color descriptor ...
21 
Summary of comic character extraction 
17/10/14 - christophe-rigaud.com 
● Supervised approaches 
● Character spotting...
22 
Hypothesis from speech balloon tail position and direction 
● Given balloons in a panel, where are the (speaking) char...
23 
17/10/14 - christophe-rigaud.com 
Example
24 
17/10/14 - christophe-rigaud.com 
Example
25 
17/10/14 - christophe-rigaud.com 
Conclusions 
● Preliminary results 
● Highly relies on the quality of the 
tail dete...
26 
Summary of comic character extraction 
17/10/14 - christophe-rigaud.com 
● Supervised approaches 
● Character spotting...
27 
Region of interest (ROI) from simple object removal 
● Given an image from a double page of manga, can you predict whe...
28 
Region of interest (ROI) from simple object removal 
● Given an image from a double page of manga, can you predict whe...
29 
Region of interest (ROI) from simple object removal 
● Given an image from a double page of manga, can you predict whe...
30 
Region of interest (ROI) from simple object removal 
● In the same image, knowing the position of panels and balloons,...
31 
Region of interest (ROI) from simple object removal 
● Knowing the position of panels and balloons, can you predict wh...
32 
Region of interest (ROI) from simple object removal 
? 
17/10/14 - christophe-rigaud.com 
● Et voilà ! 
? ? 
? 
? 
? 
...
33 
A first test from automatic panels and balloons 
extraction... 
17/10/14 - christophe-rigaud.com
34 
Original image 
17/10/14 - christophe-rigaud.com
35 
Image masked 
17/10/14 - christophe-rigaud.com
36 
Image masked + distance transform 
17/10/14 - christophe-rigaud.com
39 
17/10/14 - christophe-rigaud.com 
To be continued...
40 
17/10/14 - christophe-rigaud.com 
Graph-based approach 
● Presented by Nam Le Thanh
41 
Live demo: real time panels and balloons extraction 
17/10/14 - christophe-rigaud.com
42 
https://github.com/crigaud/publication/tree/master/2014/TALK/intelligent_media_processing_group 
17/10/14 - christophe...
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Detection of comic characters in comic books and manga

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State of the art methods for comic character (people) localization in comic book images and manga.

Published in: Science
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Detection of comic characters in comic books and manga

  1. 1. Detection of comic characters in comic books and manga 17/10/14 - christophe-rigaud.com
  2. 2. 2 17/10/14 - christophe-rigaud.com Presentation Advisers ● Jean-Christophe Burie & Jean-Marc Ogier (L3i, La Rochelle, France) ● Dimosthenis Karatzas (CVC, Barcelona, Spain) eBDtheque project ● Comic book image processing and understanding ● Cultural heritage in many countries ● Paper ↔ digital comic book conversion enhancement ● New usages using the new technologies Applications ● Text/image search, augmented reading, reflowing... France Spain
  3. 3. 3 What researchers can do for the paper to digital transition? Researchers Paper world Digital world Digital world 17/10/14 - christophe-rigaud.com
  4. 4. 4 Researchers Image credits: contributors of the eBDtheque dataset 17/10/14 - christophe-rigaud.com
  5. 5. 5 17/10/14 - christophe-rigaud.com Balloon classification Speaker localization Text timestamps Tone and pitch Scene understanding Layout analysis Panel retrieval Reflowing De-hyphenation Speech synthesis Language analysis Translation assistance Pose retrieval Facial expression Relationship retrieval Character localization and recognition Researchers PPAANNEELLSS
  6. 6. 6 17/10/14 - christophe-rigaud.com Balloon classification Speaker localization Text timestamps Tone and pitch Scene understanding Layout analysis Panel retrieval Reflowing De-hyphenation Speech synthesis Language analysis Translation assistance Pose retrieval Facial expression Relationship retrieval Character localization and recognition Researchers TTEEXXTT
  7. 7. 7 17/10/14 - christophe-rigaud.com Balloon classification Speaker localization Text timestamps Tone and pitch Scene understanding Layout analysis Panel retrieval Reflowing De-hyphenation Speech synthesis Language analysis Translation assistance Pose retrieval Facial expression Relationship retrieval Character localization and recognition Researchers BBAALLLLOOOONNSS
  8. 8. 8 CCHHAARRAACCTTEERRSS 17/10/14 - christophe-rigaud.com Balloon classification Speaker localization Text timestamps Tone and pitch Scene understanding Layout analysis Panel retrieval Reflowing De-hyphenation Speech synthesis Language analysis Translation assistance Pose retrieval Facial expression Relationship retrieval Character localization and recognition Researchers
  9. 9. 9 Challenges of comics analysis ● Variation of comic book styles ● Printing & scanning method changes over time (press, ink-jet, computer-based) ● Diversity of information to extract ● A lot of semantic relations to retrieve (element's relationships, text 17/10/14 - christophe-rigaud.com meaning)
  10. 10. 11 Summary of comic character extraction 17/10/14 - christophe-rigaud.com ● Supervised approaches ● Character spotting given an example ● Unsupervised approaches ● Hypothesis from speech balloon tail position and orientation ● Region of interest from simple object removal ● Graph­based approach (Nam)
  11. 11. 12 Summary of comic character extraction 17/10/14 - christophe-rigaud.com ● Supervised approaches ● Character spotting given an example ● Unsupervised approaches ● Hypothesis from speech balloon tail position and orientation ● Region of interest from simple object removal ● Graph­based approach (Nam)
  12. 12. 13 Character spotting given an example [5] ● Aim: retrieve all the instances (apparitions) of a given character in all the pages of a comic book title/album/collection 17/10/14 - christophe-rigaud.com ● Method summary: 1) Reduction of the number of colors 2) Get the colors of the query example (user interaction) 3) Compute the user query descriptor 4) Spot similar character instances [5] C. Rigaud, D. Karatzas, J-C Burie, J-M Ogier Color descriptor for content-based drawing retrieval DAS'14
  13. 13. 14 1) Color reduction/quantization N>10000 N=256 N=32 17/10/14 - christophe-rigaud.com
  14. 14. 15 17/10/14 - christophe-rigaud.com 2) User query
  15. 15. 16 3) Color selection: occurrence level 17/10/14 - christophe-rigaud.com
  16. 16. 17 3) Color selection: occurrence + discriminality levels 17/10/14 - christophe-rigaud.com Top 3 colors
  17. 17. 18 4) Character spotting: example 17/10/14 - christophe-rigaud.com User input Image credits: (Prunelle, la fille du cyclope, Ankama, 2010 Descriptor
  18. 18. 19 4) Character spotting: example correct detections wrong detections 17/10/14 - christophe-rigaud.com
  19. 19. 20 17/10/14 - christophe-rigaud.com Conclusions ● Contributions ● Content Based Drawing Retrieval ● Color descriptor robust to scale, rotation, translation, deformation and occlusion ● Benefit of redundant information ● Limitations ● Colored comics ● Number of color (quantization) ● Requires one example of each character Query Correct Wrong Result examples
  20. 20. 21 Summary of comic character extraction 17/10/14 - christophe-rigaud.com ● Supervised approaches ● Character spotting given an example ● Unsupervised approaches ● Hypothesis from speech balloon tail position and orientation ● Region of interest from simple object removal ● Graph­based approach (Nam)
  21. 21. 22 Hypothesis from speech balloon tail position and direction ● Given balloons in a panel, where are the (speaking) characters? 17/10/14 - christophe-rigaud.com
  22. 22. 23 17/10/14 - christophe-rigaud.com Example
  23. 23. 24 17/10/14 - christophe-rigaud.com Example
  24. 24. 25 17/10/14 - christophe-rigaud.com Conclusions ● Preliminary results ● Highly relies on the quality of the tail detection ● Only for “speaking” characters (others can be spotted) ● Implicitly retrieves the relationship between balloon and character
  25. 25. 26 Summary of comic character extraction 17/10/14 - christophe-rigaud.com ● Supervised approaches ● Character spotting given an example ● Unsupervised approaches ● Hypothesis from speech balloon tail position and orientation ● Region of interest from simple object removal ● Graph­based approach (Nam)
  26. 26. 27 Region of interest (ROI) from simple object removal ● Given an image from a double page of manga, can you predict where the 17/10/14 - christophe-rigaud.com characters are?
  27. 27. 28 Region of interest (ROI) from simple object removal ● Given an image from a double page of manga, can you predict where the ? ? 17/10/14 - christophe-rigaud.com characters are? ? ? ? ? ? ? ? ? ? ?
  28. 28. 29 Region of interest (ROI) from simple object removal ● Given an image from a double page of manga, can you predict where the 17/10/14 - christophe-rigaud.com characters are? ? ? ? ? ? ? ? ? 42% correct ? ? ? ? Image credits: Yasuhisa Hara, "Kingdom", Shueisha, since 2006.
  29. 29. 30 Region of interest (ROI) from simple object removal ● In the same image, knowing the position of panels and balloons, can you predict where the comic characters are? 17/10/14 - christophe-rigaud.com
  30. 30. 31 Region of interest (ROI) from simple object removal ● Knowing the position of panels and balloons, can you predict where the ? 17/10/14 - christophe-rigaud.com comic characters are? ? ? ? ? ? ? ? ??? ?
  31. 31. 32 Region of interest (ROI) from simple object removal ? 17/10/14 - christophe-rigaud.com ● Et voilà ! ? ? ? ? ? ? ? ?? ? ? 83% correct
  32. 32. 33 A first test from automatic panels and balloons extraction... 17/10/14 - christophe-rigaud.com
  33. 33. 34 Original image 17/10/14 - christophe-rigaud.com
  34. 34. 35 Image masked 17/10/14 - christophe-rigaud.com
  35. 35. 36 Image masked + distance transform 17/10/14 - christophe-rigaud.com
  36. 36. 39 17/10/14 - christophe-rigaud.com To be continued...
  37. 37. 40 17/10/14 - christophe-rigaud.com Graph-based approach ● Presented by Nam Le Thanh
  38. 38. 41 Live demo: real time panels and balloons extraction 17/10/14 - christophe-rigaud.com
  39. 39. 42 https://github.com/crigaud/publication/tree/master/2014/TALK/intelligent_media_processing_group 17/10/14 - christophe-rigaud.com

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