Next Article in Journal
Identification of Object Dynamics Using Hand Worn Motion and Force Sensors
Next Article in Special Issue
Novel Resistance Measurement Method: Analysis of Accuracy and Thermal Dependence with Applications in Fiber Materials
Previous Article in Journal
Estimating Leaf Area Index (LAI) in Vineyards Using the PocketLAI Smart-App
Previous Article in Special Issue
On Gait Analysis Estimation Errors Using Force Sensors on a Smart Rollator
Article Menu

Export Article

Open AccessArticle
Sensors 2016, 16(12), 2003; doi:10.3390/s16122003

Data-Driven Multiresolution Camera Using the Foveal Adaptive Pyramid

Dpto. Tecnología Electrónica, University of Málaga, Campus de Teatinos, 29071 Málaga, Spain
*
Author to whom correspondence should be addressed.
Academic Editor: Gonzalo Pajares Martinsanz
Received: 23 August 2016 / Revised: 16 November 2016 / Accepted: 18 November 2016 / Published: 26 November 2016
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2016)
View Full-Text   |   Download PDF [2526 KB, uploaded 26 November 2016]   |  

Abstract

There exist image processing applications, such as tracking or pattern recognition, that are not necessarily precise enough to maintain the same resolution across the whole image sensor. In fact, they must only keep it as high as possible in a relatively small region, but covering a wide field of view. This is the aim of foveal vision systems. Briefly, they propose to sense a large field of view at a spatially-variant resolution: one relatively small region, the fovea, is mapped at a high resolution, while the rest of the image is captured at a lower resolution. In these systems, this fovea must be moved, from one region of interest to another one, to scan a visual scene. It is interesting that the part of the scene that is covered by the fovea should not be merely spatial, but closely related to perceptual objects. Segmentation and attention are then intimately tied together: while the segmentation process is responsible for extracting perceptively-coherent entities from the scene (proto-objects), attention can guide segmentation. From this loop, the concept of foveal attention arises. This work proposes a hardware system for mapping a uniformly-sampled sensor to a space-variant one. Furthermore, this mapping is tied with a software-based, foveal attention mechanism that takes as input the stream of generated foveal images. The whole hardware/software architecture has been designed to be embedded within an all programmable system on chip (AP SoC). Our results show the flexibility of the data port for exchanging information between the mapping and attention parts of the architecture and the good performance rates of the mapping procedure. Experimental evaluation also demonstrates that the segmentation method and the attention model provide results comparable to other more computationally-expensive algorithms. View Full-Text
Keywords: foveal images; irregular pyramids; hierarchical segmentation; visual attention; hardware/software co-design; AP SoC foveal images; irregular pyramids; hierarchical segmentation; visual attention; hardware/software co-design; AP SoC
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

González, M.; Sánchez-Pedraza, A.; Marfil, R.; Rodríguez, J.A.; Bandera, A. Data-Driven Multiresolution Camera Using the Foveal Adaptive Pyramid. Sensors 2016, 16, 2003.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top