Sorry, you need to enable JavaScript to visit this website.

MULTI-VIEW DISTRIBUTED SOURCE CODING OF BINARY FEATURES FOR VISUAL SENSOR NETWORKS

Citation Author(s):
Catarina Brites, Fernando Pereira, João Ascenso
Submitted by:
Nuno Cabral Monteiro
Last updated:
19 March 2016 - 7:43am
Document Type:
Poster
Document Year:
2016
Event:
Presenters Name:
Nuno Monteiro

Abstract 

Abstract: 

This is an overview poster on recent research of visual analysis algorithms in visual sensor networks. With the following 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.

up
0 users have voted:

Dataset Files

Poster_ICASSP16_nmonteiro.pdf

(565)