Automatic generation of funny cartoons diary for everyday mobile life

Injee Song, Myung Chul Jung, Sung Bae Cho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


The notable developments in pervasive and wireless technology enable us to collect enormous sensor data from each individual. With contextaware technologies, these data can be summarized into context data which support each individual's reflection process of one's own memory and communication process between the individuals. To improve reflection and communication, this paper proposes an automatic cartoon generation method for fun. Cartoon is a suitable medium for the reflection and the communication of one's own memory, especially for the emotional part. By considering the fun when generating cartoons, the advantage of the cartoon can be boosted. For the funnier cartoon, diversity and consistency are considered during the cartoon generation. For the automated generation of diverse and consistent cartoon, context data which represent the user's behavioral and mental status are exploited. From these context information and predefined user profile, the similarity between context and cartoon image is calculated. The cartoon image with high similarity is selected to be merged into cartoon cuts. Selected cartoon cuts are arranged with the constraints for the consistency of cartoon story. To evaluate the diversity and consistency of the proposed method, several operational examples are employed.

Original languageEnglish
Title of host publicationAI 2006
Subtitle of host publicationAdvances in Artificial Intelligence - 19th Australian Joint Conference on Artificial Intelligence, Proceedings
PublisherSpringer Verlag
Number of pages10
ISBN (Print)9783540497875
Publication statusPublished - 2006
Event19th Australian Joint Conference onArtificial Intelligence, AI 2006 - Hobart, TAS, Australia
Duration: 2006 Dec 42006 Dec 8

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4304 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other19th Australian Joint Conference onArtificial Intelligence, AI 2006
CityHobart, TAS

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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