Distributed On-line Multi-view Video Summarization in Video Sensor Networks
Date Issued
2014
Date
2014
Author(s)
Ou, Shun-Hsing
Abstract
With the rapid development in video processing and sensing technologies, and the revolution of Internet-of-things (IoT) or machine-to-machine (M2M), the applications of video sensor networks become wider. However, due to the high data rate of video data, it is becoming impossible for all sensors to stream video to the server. Furthermore, in wireless video sensor networks, precise video data filtering is also the key to enable low-power wireless video sensors.
Video summarization, or video abstraction, which aims to generate a short representation of the original videos, provides an excellent solution for video management. There are usually a lot of useless and redundant data in the video taken by video sensor networks, such as the redundancy in the temporal domain of the single camera, or the redundancy in spatial domain across a group of related cameras. Streaming all those video data wastes transmission bandwidth, storage spaces, and the precise energy on wireless video sensors.
In this thesis, we proposed to apply multi-view video summarization in video sensor networks to help reducing transmission bandwidth, storage spaces, and the power consumption on wireless video sensors. The video data can be reduced while keeping important information. However, most existing summarization methods are off-line and centralized, which means all videos are still required to be streamed back the server before performing summarization. Furthermore, the computation complexity is usually high, making them not suitable to operate on video sensors.
To address the above issues, two distributed on-line multi-view video summarization methods are proposed. Both methods can operate under low computational resources. Experiments show that although processing video under much more difficult constraints, the proposed distributed on-line summarization methods still generate comparable results compared with other centralized or off-line methods. Important events can be kept while reducing large amount of video data. Power analysis of the system also shows that a significant amount of energy can be saved.
Besides simulation, we also implement our own wireless video sensor networks with the summarization system. The implementation further validates our ideas of the proposed summarization methods.
Subjects
視訊摘要
視訊感測器網路
Type
thesis
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