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. © 2012 Springer-Verlag.

Instant scene recognition on mobile platform

Ravi' D.;
2012-01-01

Abstract

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. © 2012 Springer-Verlag.
2012
9783642338847
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3313023
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? ND
social impact