TY - GEN
T1 - Data mining for image/video processing
T2 - 2008 International Conference on Image and Video Retrieval, CIVR 2008
AU - Han, Jiawei
PY - 2008
Y1 - 2008
N2 - Image and video data contains abundant, rich information for data miners to explore. On one hand, the rich literature on image and video data analysis will naturally provide many advanced methods that may help mining other kinds of data. On the other hand, recent research on data mining will also provide some new, interesting methods that may benefit image and video data retrieval and analysis. In this talk we explore the latter, and discuss whether the new results obtained in data mining research could be useful in image and video data retrieval and analysis. Our discussion will be focused on the following aspects: (1) how frequent pattern, sequential pattern, and structural pattern analysis methods may help image and video data analysis; (2) how data mining may help construction of effective and efficient indexing and similarity search mechanisms for image and video retrieval; (3) how discriminative pattern-based classification methods may shed new light on image and video classification; and (4) how pattern-based analysis methods may help high-dimensional clustering in image and video analysis. Our goal is to promote collaborative research between these two research communities.
AB - Image and video data contains abundant, rich information for data miners to explore. On one hand, the rich literature on image and video data analysis will naturally provide many advanced methods that may help mining other kinds of data. On the other hand, recent research on data mining will also provide some new, interesting methods that may benefit image and video data retrieval and analysis. In this talk we explore the latter, and discuss whether the new results obtained in data mining research could be useful in image and video data retrieval and analysis. Our discussion will be focused on the following aspects: (1) how frequent pattern, sequential pattern, and structural pattern analysis methods may help image and video data analysis; (2) how data mining may help construction of effective and efficient indexing and similarity search mechanisms for image and video retrieval; (3) how discriminative pattern-based classification methods may shed new light on image and video classification; and (4) how pattern-based analysis methods may help high-dimensional clustering in image and video analysis. Our goal is to promote collaborative research between these two research communities.
KW - Data mining
KW - Image and video processing
KW - Interdisciplinary research
UR - http://www.scopus.com/inward/record.url?scp=57549089266&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=57549089266&partnerID=8YFLogxK
U2 - 10.1145/1386352.1386353
DO - 10.1145/1386352.1386353
M3 - Conference contribution
AN - SCOPUS:57549089266
SN - 9781605580708
T3 - CIVR 2008 - Proceedings of the International Conference on Content-based Image and Video Retrieval
SP - 1
EP - 2
BT - CIVR 2008 - Proceedings of the International Conference on Content-based Image and Video Retrieval
Y2 - 7 July 2008 through 9 July 2008
ER -