中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
基于字典选择的机器人在线场景语义浓缩

文献类型:期刊论文

作者黄疆坪; 丛杨; 高宏伟; 唐延东; 于海斌
刊名科学通报
出版日期2013
卷号58期号:S2页码:112-120
关键词字典选择 语义浓缩 机器人 在线学习
ISSN号0023-074X
其他题名Online semantic condense video in robotic scene via dictional selection
产权排序1
通讯作者丛杨
中文摘要视频数据是信息存储的重要手段,但是很多时候(如机器人运动时采集的视频、监控相机记录的视频等),视频帧与帧之间相似度高,造成信息冗余,为信息的存储、查询、传输等带来困难.本文设计了一种语义浓缩算法,通过提取视频中的关键帧,实现快速、准确感知视频内容的目的.该算法首先采用背景建模方法从原始视频中提取包含重要信息的连续前景视频段,去除信息量较少的背景帧,然后通过采用视频语义分割方法将前景视频段分割得到一系列子视频,将从子视频的每一帧中提取出的特征构成原始字典,采用字典选择方法提取出关键帧.本文方法针对导航/监控视频,使用背景建模过滤无用信息,通过视频语义分割方法可处理不限长度的视频,而所选取的图像特征和字典选择方法则灵活有效地提取出有意义的关键帧.在实验中,通过对移动/固定平台视频的测试,并与人工标识及其他语义浓缩方法进行比较,证明本算法的重构误差较小,可以准确地提取视频中的关键帧.
英文摘要Video data are important representatives for information storage. However, high similarity always exists among the video frames in many cases, such as robot videos, some kind of surveillance videos, and so on. This will lead to information redundancy, and futher will cause problems in information storage, query, and transfer. In this paper, we present an algorithm for video semantic enrichment. This method may perceive the video content quickly and accurately by extracting the key frames from video sequences. First, we extract the continuous foreground segments from the original video sequences to remove the background frames. Then, we segment the foreground to be a series of sub video sequences by the shot boundary detection process. The features extracted from the sub video sequences constitute the original dectionary. Finally, we select the key frames with a dictionary selection process. By removing the useless information with a background model, our method can deal with arbitrary length videos by the shot boundary detection. The meaningful key frames can be extracted based on the image features and dictionary seletion method. Compared with the artificial identification method and the baseline algorithms, the experiment results verify that our method can obtain more accurate key frames.
资助信息国家自然科学基金(61105013,61375014)资助
语种中文
源URL[http://ir.sia.cn/handle/173321/14699]  
专题沈阳自动化研究所_机器人学研究室
推荐引用方式
GB/T 7714
黄疆坪,丛杨,高宏伟,等. 基于字典选择的机器人在线场景语义浓缩[J]. 科学通报,2013,58(S2):112-120.
APA 黄疆坪,丛杨,高宏伟,唐延东,&于海斌.(2013).基于字典选择的机器人在线场景语义浓缩.科学通报,58(S2),112-120.
MLA 黄疆坪,et al."基于字典选择的机器人在线场景语义浓缩".科学通报 58.S2(2013):112-120.

入库方式: OAI收割

来源:沈阳自动化研究所

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