Title :
Intelligent home video management system
Author :
Huang, Szu-Hao ; Wu, Qi-Jiunn ; Chang, Kai-yeuh ; Lin, Hsin-Cheang ; Lai, Shang-Hong ; Wang, Wen-Hao ; Tsai, Yu-Sheng ; Chen, Chia-Lun ; Chen, Guan-Rong
Author_Institution :
Dept. of Comput. Sci., Nat. Tsing Hua Univ., Hsinchu, Taiwan
Abstract :
An integrated intelligent home video management system was proposed in this paper. Five different types of multimedia representative features were computed as the basis of the home video management system. With the aid of some machine learning techniques, such as SVM, neural network, adaboost algorithm, and the K-means clustering algorithm, we develop six main applications based on this system. These applications include detection of abnormal camera operation, shot boundary detection, fast-pan detection, face shot identification, key-frame extraction, and variable length video abstraction. Our system can help inexpert digital camcorder users manage their home video effectively in a smart way.
Keywords :
edge detection; face recognition; home automation; learning (artificial intelligence); multimedia systems; neural nets; pattern clustering; support vector machines; video cameras; K-means clustering algorithm; SVM; abnormal camera operation detection; adaboost algorithm; digital camcorder; face shot identification; fast-pan detection; intelligent home video management system; key-frame extraction; machine learning techniques; multimedia representative feature; neural network; shot boundary detection; variable length video abstraction; Clustering algorithms; Face detection; Gunshot detection systems; Home computing; Intelligent systems; Learning systems; Machine learning; Machine learning algorithms; Multimedia systems; Support vector machines;
Conference_Titel :
Information Technology: Research and Education, 2005. ITRE 2005. 3rd International Conference on
Print_ISBN :
0-7803-8932-8
DOI :
10.1109/ITRE.2005.1503094
