TY - GEN
T1 - Generating cartoon-style summary of daily life with multimedia mobile devices
AU - Cho, Sung Bae
AU - Kim, Kyung Joong
AU - Hwang, Keum Sung
PY - 2007
Y1 - 2007
N2 - Mobile devices are treasure boxes of personal information containing user's context, personal schedule, diary, short messages, photos, and videos. Also, user's usage information on Smartphone can be recorded on the device and they can be used as useful sources of high-level inference. Furthermore, stored multimedia contents can be also regarded as relevant evidences for inferring user's daily life. Without user's consciousness, the device continuously collects information and it can be used as an extended memory of human users. However, the amount of information collected is extremely huge and it is difficult to extract useful information manually from the raw data. In this paper, AniDiary (Anywhere Diary) is proposed to summarize user's daily life in a form of cartoon-style diary. Because it is not efficient to show all events in a day, selected landmark events (memorable events) are automatically converted to the cartoon images. The identification of landmark events is done by modeling causal-effect relationships among various events with a number of Bayesian networks. Experimental results on synthetic data showed that the proposed system provides an efficient and user-friendly way to summarize user's daily life.
AB - Mobile devices are treasure boxes of personal information containing user's context, personal schedule, diary, short messages, photos, and videos. Also, user's usage information on Smartphone can be recorded on the device and they can be used as useful sources of high-level inference. Furthermore, stored multimedia contents can be also regarded as relevant evidences for inferring user's daily life. Without user's consciousness, the device continuously collects information and it can be used as an extended memory of human users. However, the amount of information collected is extremely huge and it is difficult to extract useful information manually from the raw data. In this paper, AniDiary (Anywhere Diary) is proposed to summarize user's daily life in a form of cartoon-style diary. Because it is not efficient to show all events in a day, selected landmark events (memorable events) are automatically converted to the cartoon images. The identification of landmark events is done by modeling causal-effect relationships among various events with a number of Bayesian networks. Experimental results on synthetic data showed that the proposed system provides an efficient and user-friendly way to summarize user's daily life.
UR - http://www.scopus.com/inward/record.url?scp=37249007191&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=37249007191&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-73325-6_14
DO - 10.1007/978-3-540-73325-6_14
M3 - Conference contribution
AN - SCOPUS:37249007191
SN - 9783540733225
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 135
EP - 144
BT - New Trends in Applied Artificial Intelligence - 20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, lEA/AlE 2007, Proceedings
PB - Springer Verlag
T2 - 20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, lEA/AlE-2007
Y2 - 26 June 2007 through 29 June 2007
ER -