Instant Scene Context Recognition on Mobile Platform
Giovanni Maria Farinella
(University of Catania, Italy)
Abstract:
We introduce an image representation model useful to summarize the context of
the scene. The proposed image descriptor addresses the problem of real-time
scene context classification on devices with limited memory and low
computational resources (e.g., mobile and other single sensor devices). Images
are holistically represented starting from the statistics collected in the
Discrete Cosine Transform (DCT) domain. Since the DCT coefficients are usually
computed within the digital signal processor for the JPEG conversion/storage,
the proposed solution allows to obtain an instant and "free of charge"
image signature.