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Static Multi-device Load Balancing for OpenCL

This paper presents the Load Balancing for OpenCL (lbcl) library, devoted to automatically solve load balancing issues on both multi-platform and heterogeneous environments. Using this library, a single kernel can be executed on a set of heterogeneous devices, giving each device an amount of work proportional to its computing power. A wrapper has been developed so the library can balance the workload of an existing application not only without introducing any changes into its source code, but without any recompilation stage. Also a general OpenCL profiler has been developed to easily do a detailed profiling of the obtained results.

A study of Zernike invariants for content-based image retrieval

This paper presents a study about the application of Zernike invariants to content-based Image Retrieval for 2D color images. Zernike invariants have been chosen because of their good performance for object recognition. Taking into account the good results achieved in previous CBIR experiments with color based primitives using a multiresolution representation of the visual contents, this paper presents the application of a wavelet transform to the images in order to obtain a multiresolution representation of the shape based features studied. Experiments have been performed using two databases: the first one is a small self-made 2D color database formed by 298 RGB images and a test set with 1655 query images that has been used for preliminary tests; the second one is Also experiments using the Amsterdam Library of Object Images (ALOI), a free access database. Experimental results show the feasibility of this new approach.

Shot boundary detection using Zernike moments in multi-GPU multi-CPU architectures

This paper presents an analysis of a Multi-GPU Multi-CPU environment, along with the different possible hybrid combinations. The analysis has been performed for a shot boundary detection application, based on Zernike moments, although it is general enough to be applied to many different application areas. A deep study of the performance, bottlenecks and design challenges is carried out showing the validity of this approach and achieving very high frame per second rates. In this paper, Zernike calculations are carried out on GPUs, taking advantage of a packing strategy proposed to minimize host-device communication time.

Comparing sphere-tree generators and hierarchy updates for deformable objects collision detection

This paper presents a quantitative evaluation of the accuracy of different sphere-tree construction methods when they are used in deformable bodies. The methods evaluated are Grid (an extension of octrees), Hubbard, Adaptive Medial Axis and Spawn. We also present a new approach to update the sphere-tree hierarchy that ensures lower loss of accuracy than in traditional update techniques.

A load index and load balancing algorithm for heterogeneous clusters

This paper presents a load balancing algorithm specifically designed for heterogeneous clusters, composed of nodes with different computational capabilities. The method is based on a new index, which takes into consideration two levels of processors heterogeneity: the number of cores per node and the computational power of each core. The experimental results show that this index allows achieving balanced workload distributions even on those clusters where heterogeneity can not be neglected.

Combining activity and temporal coherence with low-level information for summarization of video rushes

This paper describes the work performed by the GMRV-URJC team as part of the TRECVid 2008 Rushes Summarization benchmark. The main goal of our approach is to obtain good results by only using low-level techniques. Using only this kind of features also has the advantage of achieving fast processing times. The work presented in this paper is a keyframe-based approach which means that all the process is built around keyframes. The proposed solution can be decomposed in three stages which are the candidate selection, candidate filtering and summary construction. We present an analysis of the results achieved in the official TRECVid tests as well as in some additional runs.

Efficient Grid-Based Video Storage and Retrieval

Different fields, such as news broadcasting (news, shows, series, etc), advertising, and medical applications, require to store a large amount of video data which can be used later on. Content-Based Video Retrieval (CBVR) systems are very attractive since they can help users to retrieve video sequences over large video databases with respect to some specific topic, character or place. In most cases, stored videos belong to different organizations and have a quite demanding storage capacity. These features fit in a natural way into the concept of grid computing, that provides a great computing and storage capacity thanks to the use of heterogeneous resources put together by the cooperation and resource sharing among different institutions. This paper presents a Grid and Content-based VIdeo Retrieval (GCViR) system that offers a good cost/performance ratio to select the most suitable grid resources for data storage in order to store and retrieve large video data providing flexibility and scalability. An evaluation shows the feasibility and benefits of this approach.

Video shot extraction on parallel architectures

One of the main objectives of Content-based Multimedia Retrieval systems is the automation of the information extraction process from raw data. When dealing with video data, the first step is to perform a temporal video segmentation in order to make a shot decomposition of the video content. From a computational point of view, this is a very high demanding task and algorithm optimization must be seeked. This paper presents a comparison between two different parallel programming paradigms: shared-memory communication and distributed memory processing using the message passing paradigm. Taking into account the software solutions, experimental results are collected over two alternative parallel architectures: a shared-memory symmetric multiprocessor and a cluster. This paper analyzes the performance achieved from the viewpoints of speed and scalability.

RF Inhomogeneity Correction Algorithm in Magnetic Resonance Imaging

MR images usually present grey level inhomogeneities which are a problem of significant importance. Eliminating these inhomogeneities is not an easy problem and has been studied and discussed in several previous publications. Most of those approaches are based on segmentation processes. The algorithm presented in this paper has the advantage that it does not involve any segmentation step. Instead, a interpolating polynomial model based on a Gabor transform was used to construct a filter that can be used in order to correct these inhomogeneities. The results obtained are really good and shows that the grey-level inhomogeneities can be corrected without segmentation.

Musical representation of dendritic spine distribution: a new exploratory tool.

Dendritic spines are small protrusions along the dendrites of many types of neurons in the central nervous system and represent the major target of excitatory synapses. For this reason, numerous anatomical, physiological and computational studies have focused on these structures. In the cerebral cortex the most abundant and characteristic neuronal type are pyramidal cells (about 85 % of all neurons) and their dendritic spines are the main postsynaptic target of excitatory glutamatergic synapses. Thus, our understanding of the synaptic organization of the cerebral cortex largely depends on the knowledge regarding synaptic inputs to dendritic spines of pyramidal cells. Much of the structural data on dendritic spines produced by modern neuroscience involves the quantitative analysis of image stacks from light and electron microscopy, using standard statistical and mathematical tools and software developed to this end. Here, we present a new method with musical feedback for exploring dendritic spine morphology and distribution patterns in pyramidal neurons. We demonstrate that audio analysis of spiny dendrites with apparently similar morphology may “sound” quite different, revealing anatomical substrates that are not apparent from simple visual inspection. These morphological/music translations may serve as a guide for further mathematical analysis of the design of the pyramidal neurons and of spiny dendrites in general.