Header

UZH-Logo

Maintenance Infos

Real-time depth from focus on a programmable focal plane processor


Martel, Julien N P; Muller, Lorenz K; Carey, Stephen J; Muller, Jonathan; Sandamirskaya, Yulia; Dudek, Piotr (2018). Real-time depth from focus on a programmable focal plane processor. IEEE Transactions on Circuits and Systems - Part I: Regular Papers, 65(3):925-934.

Abstract

Visual input can be used to recover the 3-D structure of a scene by estimating distances (depth) to the observer. Depth estimation is performed in various applications, such as robotics, autonomous driving, or surveillance. We present a low-power, compact, passive, and static imaging system that computes a semi-dense depth map in real time for a wide range of depths. This is achieved by using a focus-tunable liquid lens to sweep the optical power of the system at a high frequency, computing depth from focus on a mixed-signal programmable focal-plane processor. The use of local and highly parallel process- ing directly on the focal plane removes the sensor-processor bandwidth limitations typical in conventional imaging and processor technologies and allows real-time performance to be achieved.

Abstract

Visual input can be used to recover the 3-D structure of a scene by estimating distances (depth) to the observer. Depth estimation is performed in various applications, such as robotics, autonomous driving, or surveillance. We present a low-power, compact, passive, and static imaging system that computes a semi-dense depth map in real time for a wide range of depths. This is achieved by using a focus-tunable liquid lens to sweep the optical power of the system at a high frequency, computing depth from focus on a mixed-signal programmable focal-plane processor. The use of local and highly parallel process- ing directly on the focal plane removes the sensor-processor bandwidth limitations typical in conventional imaging and processor technologies and allows real-time performance to be achieved.

Statistics

Citations

Dimensions.ai Metrics
2 citations in Web of Science®
2 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

88 downloads since deposited on 01 Mar 2018
80 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Scopus Subject Areas:Physical Sciences > Electrical and Electronic Engineering
Language:English
Date:2018
Deposited On:01 Mar 2018 12:08
Last Modified:29 Jul 2020 07:00
Publisher:Institute of Electrical and Electronics Engineers
Series Name:IEEE Transactions on Circuits and Systems I: Regular Papers
ISSN:1057-7122
Additional Information:© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
OA Status:Green
Publisher DOI:https://doi.org/10.1109/TCSI.2017.2753878
Official URL:http://ieeexplore.ieee.org/abstract/document/8071011/
Project Information:
  • : FunderSNSF
  • : Grant IDCRSII2_160756
  • : Project TitleHybrid CMOS/Memristive Neuromorphic Systems for Data Analytics
  • : FunderSNSF
  • : Grant ID205321_143947
  • : Project TitleBiological Information in Cortical Communication

Download

Green Open Access

Download PDF  'Real-time depth from focus on a programmable focal plane processor'.
Preview
Content: Accepted Version
Filetype: PDF
Size: 5MB