Ren, Jinchang and Jiang, J. and Feng, Y. (2010) Activity-driven content adaptation for effective video summarisation. Journal of Visual Communication and Image Representation, 21 (8). pp. 930-938.
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In this paper, we present a novel method for content adaptation and video summarization fully implemented in compressed-domain. Firstly, summarization of generic videos is modeled as the process of extracted human objects under various activities/events. Accordingly, frames are classified into five categories via fuzzy decision including shot changes (cut and gradual transitions), motion activities (camera motion and object motion) and others by using two inter-frame measurements. Secondly, human objects are detected using Haar-like features. With the detected human objects and attained frame categories, activity levels for each frame are determined to adapt with video contents. Continuous frames belonging to same category are grouped to form one activity entry as content of interest (COI) which will convert the original video into a series of activities. An overall adjustable quota is used to control the size of generated summarization for efficient streaming purpose. Upon this quota, the frames selected for summarization are determined by evenly sampling the accumulated activity levels for content adaptation. Quantitative evaluations have proved the effectiveness and efficiency of our proposed approach, which provides a more flexible and general solution for this topic as domain-specific tasks such as accurate recognition of objects can be avoided.
|Keywords:||image representation, content adaptation, video summarization, Electronic computers. Computer science, Media Technology, Signal Processing, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering|
|Subjects:||Science > Mathematics > Electronic computers. Computer science|
|Department:||Faculty of Engineering > Electronic and Electrical Engineering|
|Depositing user:||Pure Administrator|
|Date Deposited:||16 Mar 2011 14:37|
|Last modified:||09 Jan 2017 01:44|