Publication: Towards a Smart Selection of Hybrid Platforms for Multimedia Processing
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2016-02
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Abstract
Nowadays, images and videos have been present everywhere, they can come directly from camera, mobile devices
or from other peoples that share their images and videos. The latter are used to illustrate different objects in a
large number of situations. This makes from image and video processing algorithms a very important tool used for
various domains related to computer vision such as video surveillance, medical imaging and database (images and
videos) indexation methods. The performance of these algorithms have been so reduced due the the high intensive
computation required when using new image and video standards. In this paper, we propose a new framework that
allows users to select in a smart and efficient way the processing units (GPU or/and CPU) within heterogeneous
systems, when treating different kinds of multimedia objects : single image, multiple images, multiple videos and
video in real time. The framework disposes of different image and video primitive functions that are implemented
on GPU, such as shape (silhouette) detection, motion tracking using optical flow estimation, edges and corners
detection. We have exploited these functions for several situations such as indexing videos, segmenting vertebrae
in in X-ray and MR images, detecting and localizing event in multi-user scenarios. Experimentation showed
interesting accelerations ranging from 6 to 118, by comparison with sequential implementations. Moreover, the
parallel and heterogeneous implementations offered lower power consumption as a result for the fast treatment.
Description
Proceedings of the First PhD Symposium on Sustainable Ultrascale
Computing Systems (NESUS PhD 2016) Timisoara, Romania. February 8-11, 2016.
Keywords
GPU, Heterogeneous architectures, Image and video processing, Medical imaging, Motion tracking
Bibliographic citation
Carretero Pérez, Jesús; et.al. (eds.). (2016). Proceedings of the First PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016). Timisoara, Romania. Universidad Carlos III de Madrid, ARCOS. Pp. 5-8.