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On the performances of computer vision algorithms on mobile platforms

Conference Paper
Publication Date:
2012
abstract:
Computer Vision enables mobile devices to extract the meaning of the observed scene from the information acquired with the onboard sensor cameras. Nowadays, there is a growing interest in Computer Vision algorithms able to work on mobile platform (e.g., phone camera, point-and-shot-camera, etc.). Indeed, bringing Computer Vision capabilities on mobile devices open new opportunities in different application contexts. The implementation of vision algorithms on mobile devices is still a challenging task since these devices have poor image sensors and optics as well as limited processing power. In this paper we have considered different algorithms covering classic Computer Vision tasks: keypoint extraction, face detection, image segmentation. Several tests have been done to compare the performances of the involved mobile platforms: Nokia N900, LG Optimus One, Samsung Galaxy SII. © 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
Iris type:
14.d.3 Contributi in extenso in Atti di convegno
Keywords:
Computer Vision; Face Detection; Feature Extraction; Image Segmentation; Mobile Devices
List of contributors:
Battiato, S.; Farinella, G. M.; Messina, E.; Puglisi, G.; Ravi', D.; Capra, A.; Tomaselli, V.
Authors of the University:
RAVI' Daniele
Handle:
https://iris.unime.it/handle/11570/3313016
Book title:
Proceedings of SPIE - The International Society for Optical Engineering
Published in:
PROCEEDINGS OF SPIE, THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING
Journal
PROCEEDINGS OF SPIE, THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING
Series
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