Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: May 24, 2026

Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

Selective change driven imaging: a biomimetic visual sensing strategy.

Jose A Boluda1, Pedro Zuccarello, Fernando Pardo

  • 1Departament d'Informàtica, Escola Tècnica Superior d'Enginyeria, Universitat de València, Avd. Vicente Andres Estellés, s/n, 46100 Burjassot, València, Spain. Jose.A.Boluda@uv.es

Sensors (Basel, Switzerland)
|February 21, 2012
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Biomass-Derived Solvents and Low-GWP Refrigerants as Working Fluids for Sustainable Absorption Refrigeration.

ACS sustainable chemistry & engineering·2025
Same author

Neoadjuvant therapy versus upfront surgery in resectable pancreatic cancer: reconstructed patient-level meta-analysis of randomized clinical trials.

BJS open·2024
Same author

New insights into the regulation of bile acids synthesis during the early stages of liver regeneration: A human and experimental study.

Biochimica et biophysica acta. Molecular basis of disease·2024
Same author

Short- and long-term outcomes after distal pancreatectomy with radiologic infiltration of splenic vessels for pancreatic ductal adenocarcinoma.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract·2024
Same author

Textbook outcome in distal pancreatectomy: A multicenter study.

Surgery·2023
Same author

Mapping early serum proteome signatures of liver regeneration in living donor liver transplant cases.

BioFactors (Oxford, England)·2023
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Selective Change Driven (SCD) Vision accelerates image sensing using a novel CMOS sensor that reports changed pixels. This biomimetic approach shifts processing from full frames to a data flow, pixel-based paradigm for faster image acquisition.

Area of Science:

  • Computer Vision
  • Biomimetic Engineering
  • Image Processing

Background:

  • Traditional image sensing relies on full-frame processing, which can be inefficient for dynamic scenes.
  • Biologically inspired approaches offer potential for faster and more efficient visual data handling.

Purpose of the Study:

  • To introduce and describe Selective Change Driven (SCD) Vision, a novel image sensing strategy.
  • To highlight the advantages of SCD Vision in speeding up image acquisition and processing.

Main Methods:

  • Development of a new CMOS image sensor for SCD Vision.
  • Implementation of a data flow, pixel-based processing paradigm.
  • Comparison with traditional full-frame image processing methodologies.
Keywords:
CMOS image sensorbiomimeticsevent-based visionmotion analysis

More Related Videos

Long-Term Imaging of Identified Neural Populations using Microprisms in Freely Moving and Head-Fixed Animals
06:25

Long-Term Imaging of Identified Neural Populations using Microprisms in Freely Moving and Head-Fixed Animals

Published on: January 19, 2024

Two-photon Calcium Imaging in Mice Navigating a Virtual Reality Environment
08:12

Two-photon Calcium Imaging in Mice Navigating a Virtual Reality Environment

Published on: February 20, 2014

Related Experiment Videos

Last Updated: May 24, 2026

Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

Long-Term Imaging of Identified Neural Populations using Microprisms in Freely Moving and Head-Fixed Animals
06:25

Long-Term Imaging of Identified Neural Populations using Microprisms in Freely Moving and Head-Fixed Animals

Published on: January 19, 2024

Two-photon Calcium Imaging in Mice Navigating a Virtual Reality Environment
08:12

Two-photon Calcium Imaging in Mice Navigating a Virtual Reality Environment

Published on: February 20, 2014

Main Results:

  • SCD Vision significantly speeds up image sensing compared to conventional methods.
  • The new CMOS sensor efficiently delivers changed pixels, ordered by magnitude.
  • The data flow processing paradigm enhances overall system efficiency.

Conclusions:

  • SCD Vision represents a significant advancement in image sensing technology.
  • The biomimetic approach offers a promising direction for future image acquisition and processing systems.