Video hierarchical structure mining

被引：1

作者：

Fu, Chang-Jian ^{[1
,2
]}

Li, Guo-Hui ^{[1
]}

Wu, Jun-Tao ^{[1
]}

Fu, Chang-Jian ^{[1
,2
]}

机构：

[1] Natl Univ Def Technol, Sch Informat Syst & Management, Changsha 410073, Hunan, Peoples R China

[2] Xiangtan Univ, Sch Business, Xiangtan 411105, Peoples R China

来源：

2006 INTERNATIONAL CONFERENCE ON COMMUNICATIONS, CIRCUITS AND SYSTEMS PROCEEDINGS, VOLS 1-4: VOL 1: SIGNAL PROCESSING | 2006年

基金：

中国国家自然科学基金;

关键词：

D O I：

10.1109/ICCCAS.2006.284924

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 [模式识别与智能系统]; 0812 [计算机科学与技术]; 0835 [软件工程]; 1405 [智能科学与技术];

摘要：

To structuralize video streams plays an important role in the processing of video. The basic structure for video is a hierarchical structure which consists of four kinds of components, namely frame, shot, scene, and video program. A simple framework for video hierarchical structure mining is to partition continuous video frames into discrete physical shots, extract features from video shots and construct scene structure based on shots. In this paper, two crucial algorithms of video hierarchical structure mining, Multi-features Shot Clustering (NISC) and Scene Change Detection (SCD), are proposed-based on color, texture and semantic similarity of shot Our experimental results demonstrate the performance of SCD is better than that of MSC.

引用

页码：2150 / +

页数：2

共 13 条

[1]

Toward automatic extraction of expressive elements from motion pictures: Tempo [J].