PRedictive Intelligent Maintenance Enabler
|1 September 2016|
|1 March 2021|
|More info (PDF):|
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|Pablo del Moral|
Involved internal personnel
Involved external personnel
Swedish Research Council, Research Project No: 2016-03497
This project relates broadly to ocular biometrics in unconstrained sensing environments. Particularly, to methods for reliable detection/segmentation of ocular regions, and reconstruction of low-resolution images. The specific research objectives are:
- Detection of ocular region in unconstrained sensing environments under variations in scale, illumination, pose, low resolution, noise, etc. This is novel, since the vast majority of ocular recognition works have relied on manual annotation.
- Super-resolution reconstruction of ocular images. It may be used to iteratively improve detection (which may improve reconstruction further too), and ultimately to get better recognition accuracy thanks to enhanced image quality. Despite low resolution is frequent in relaxed environments, few ocular reconstruction works exist.
- Ocular recognition by case studies using data at a distance and on the move. Fundamental research contributions can be greatly benefited with practical applications in mind, since they enable to assess merits of the developments. We will concentrate on two cases: cooperative scenario with personal devices (smartphone), and uncooperative with surveillance cameras.
A primary consequence will be facilitated user interaction by enabling the use of data acquired in a wide range of operational conditions. More comfort and convenience can be achieved thanks to the use of own devices and natural interaction patterns with digital systems.