Instant scene recognition on mobile platform

Sebastiano Battiato, Giovanni Maria Farinella, Mirko Guarnera, Daniele Ravì, Valeria Tomaselli

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

5 Citations (Scopus)


Scene recognition is extremely useful to improve different tasks involved in the Image Generation Pipeline of single sensor mobile devices (e.g., white balancing, autoexposure, etc). This demo showcases our scene recognition engine implemented on a Nokia N900 smartphone. The engine exploits an image representation directly obtainable in the IGP of mobile devices. The demo works in realtime and it is able to discriminate among different classes of scenes. The framework is built by employing the FCam API to have an easy and precise control of the mobile digital camera. Each acquired image (or frame of a video) is holistically represented starting from the statistics collected on DCT domain. This allow instant and "free of charge" feature extraction process since the DCT is always computed into the IGP of a mobile for storage purposes (i.e., JPEG or MPEG format). A SVM classifier is used to perform the final inference about the context of the scene.

Original languageEnglish
Title of host publicationComputer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings
PublisherSpringer Nature
Number of pages4
EditionPART 3
ISBN (Print)9783642338847
Publication statusPublished - 2012
Externally publishedYes
Event12th European Conference on Computer Vision, ECCV 2012 - Florence, Italy
Duration: 7 Oct 201213 Oct 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume7585 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference12th European Conference on Computer Vision, ECCV 2012


  • DCT Features
  • FCam
  • Mobile Platform
  • Scene Recognition


Dive into the research topics of 'Instant scene recognition on mobile platform'. Together they form a unique fingerprint.

Cite this