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Multi-view distributed source coding of binary features for visual sensor networks | IEEE Conference Publication | IEEE Xplore

Multi-view distributed source coding of binary features for visual sensor networks


Abstract:

Visual analysis algorithms have been mostly developed for a centralized scenario where all visual data is acquired and processed at a central location. However, in visual...Show More

Abstract:

Visual analysis algorithms have been mostly developed for a centralized scenario where all visual data is acquired and processed at a central location. However, in visual sensor networks (VSN), several constraints in computational power, energy and bandwidth require a radically different approach, notably a paradigm shift from centralized to distributed visual processing. In the new paradigm, visual data is acquired and features are extracted at the sensing nodes locations to be after transmitted to enable further analysis at some central location. In such scenario, one of the key challenges is to design suitable feature coding schemes that are able to exploit the correlation among the features corresponding to (partially) overlapped views of the same visual scene. To achieve efficient coding, it is proposed to employ the distributed source coding paradigm as it does not require any communication between the sensing nodes (rather expensive in VSN) and it is parsimonious in terms of computational resources. Experimental results show that significant accuracy and compression gains (up to 37.36%) can be achieved when coding features extracted from multiple views.
Date of Conference: 20-25 March 2016
Date Added to IEEE Xplore: 19 May 2016
ISBN Information:
Electronic ISSN: 2379-190X
Conference Location: Shanghai, China

References

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