TY - GEN
T1 - Instant scene recognition on mobile platform
AU - Battiato, Sebastiano
AU - Farinella, Giovanni Maria
AU - Guarnera, Mirko
AU - Ravì, Daniele
AU - Tomaselli, Valeria
N1 - Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - DCT Features
KW - FCam
KW - Mobile Platform
KW - Scene Recognition
UR - http://www.scopus.com/inward/record.url?scp=84867708923&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-33885-4_75
DO - 10.1007/978-3-642-33885-4_75
M3 - Conference contribution
AN - SCOPUS:84867708923
SN - 9783642338847
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 655
EP - 658
BT - Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings
PB - Springer Nature
T2 - 12th European Conference on Computer Vision, ECCV 2012
Y2 - 7 October 2012 through 13 October 2012
ER -