On the performances of computer vision algorithms on mobile platforms

S. Battiato, G. M. Farinella, E. Messina, G. Puglisi, D. Ravì, A. Capra, V. Tomaselli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationProceedings of SPIE-IS and T Electronic Imaging - Digital Photography VIII
Publication statusPublished - 2012
Externally publishedYes
EventDigital Photography VIII - Burlingame, CA, United States
Duration: 23 Jan 201224 Jan 2012

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


ConferenceDigital Photography VIII
Country/TerritoryUnited States
CityBurlingame, CA


  • Computer Vision
  • Face Detection
  • Feature Extraction
  • Image Segmentation
  • Mobile Devices


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