Camera System Performance Derived from Natural Scenes
- Submitting institution
-
The University of Westminster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- qxwzq
- Type
- E - Conference contribution
- DOI
-
10.2352/ISSN.2470-1173.2020.9.IQSP-241
- Title of conference / published proceedings
- Electronic Imaging
- First page
- 241-1
- Volume
- -
- Issue
- -
- ISSN
- 2470-1173
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
-
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper introduces a novel framework for measuring digital camera performance and presents its initial validation. The proposed framework's significance is that it eliminates the use of test charts/images and traditional laboratory conditions that are necessary for precise camera performance characterisation and calibration. Instead, it uses image processing and analysis techniques to derive camera performance measurements directly from live captures of natural scenes. This innovative approach allows for live camera performance quantification and is especially relevant to CCTV, security, and autonomous driving applications (Rob Jenkin (rjenkin@nvidia.com), Principal Researcher, Camera Systems for Autonomous Driving Nvidia, USA). Won "Best Conference Paper Award".
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
