Paper Info
Title
Line image signature for scene understanding with a wearable vision system
Abstract
Wearable computer vision systems provide plenty of opportunities to develop human assistive devices. This work contributes on visual scene understanding techniques using a helmet-mounted omnidirectional vision system. The goal is to extract semantic information of the environment, such as the type of environment being traversed or the basic 3D layout of the place, to build assistive navigation systems. We propose a novel line-based image global descriptor that encloses the structure of the scene observed. This descriptor is designed with omnidirectional imagery in mind, where observed lines are longer than in conventional images. Our experiments show that the proposed descriptor can be used for indoor scene recognition comparing its results to state-of-the-art global descriptors. Besides, we demonstrate additional advantages of particular interest for wearable vision systems: higher robustness to rotation, compactness, and easier integration with other scene understanding steps.
Year
DOI
Venue
2013
10.1145/2526667.2526670
SenseCam
Keywords
Field
DocType
proposed descriptor,global descriptor,scene understanding step,assistive navigation system,visual scene understanding technique,wearable computer vision system,line image signature,wearable vision system,indoor scene recognition,human assistive device,helmet-mounted omnidirectional vision system
Computer vision,Omnidirectional antenna,Omnidirectional vision,Machine vision,Wearable computer,Robustness (computer science),Semantic information,Artificial intelligence,Geography
Conference
Citations 
PageRank 
References 
2
0.36
14
Authors
3
Name
Order
Citations
PageRank
Alejandro Rituerto1534.96
Ana C. Murillo2544.44
J. J. Guerrero320.36