Luis Pastor

Reconstruction and Simulation of Neocortical Microcircuitry

UNLABELLED We present a first-draft digital reconstruction of the microcircuitry of somatosensory cortex of juvenile rat. The reconstruction uses cellular and synaptic organizing principles to algorithmically reconstruct detailed anatomy and physiology from sparse experimental data. An objective anatomical method defines a neocortical volume of 0.29 ± 0.01 mm(3) containing ~31,000 neurons, and patch-clamp studies identify 55 layer-specific morphological and 207 morpho-electrical neuron subtypes. When digitally reconstructed neurons are positioned in the volume and synapse formation is restricted to biological bouton densities and numbers of synapses per connection, their overlapping arbors form ~8 million connections with ~37 million synapses. Simulations reproduce an array of in vitro and in vivo experiments without parameter tuning. Additionally, we find a spectrum of network states with a sharp transition from synchronous to asynchronous activity, modulated by physiological mechanisms. The spectrum of network states, dynamically reconfigured around this transition, supports diverse information processing strategies. PAPERCLIP VIDEO ABSTRACT.

Parallel CBIR implementations with load balancing algorithms

The purpose of content-based information retrieval (CBIR) systems is to retrieve, from real data stored in a database, information that is relevant to a query. When large volumes of data are considered, as it is very often the case with databases dealing with multimedia data, it may become necessary to look for parallel solutions in order to store and gain access to the available items in an efficient way.Among the range of parallel options available nowadays, clusters stand out as flexible and cost effective solutions, although the fact that they are composed of a number of independent machines makes it easy for them to become heterogeneous. This paper describes a heterogeneous cluster-oriented CBIR implementation. First, the cluster solution is analyzed without load balancing, and then, a new load balancing algorithm for this version of the CBIR system is presented.The load balancing algorithm described here is dynamic, distributed, global and highly scalable. Nodes are monitored through a load index which allows the estimation of their total amount of workload, as well as the global system state. Load balancing operations between pairs of nodes take place whenever a node finishes its job, resulting in a receptor-triggered scheme which minimizes the systems communication overhead. Globally, the CBIR cluster implementation together with the load balancing algorithm can cope effectively with varying degrees of heterogeneity within the cluster; the experiments presented within the paper show the validity of the overall strategy.Together, the CBIR implementation and the load balancing algorithm described in this paper span a new path for performant, cost effective CBIR systems which has not been explored before in the technical literature.

3D wavelet-based multiresolution object representation

This paper presents a technique for computing multiresolution shape models of 3D objects acquired as clouds of 3D points. The procedure is fully automated and is able to compute approximations for any object, overcoming sampling irregularity if present (sampling irregularity is a common feature of most 3D acquisition techniques; a typical example is stereo vision). The method described here starts by computing an intermediate mesh that meets the subdivision connectivity requirement needed to allow the computation of the wavelet transform. The mesh is then adjusted to the 3D input data using an iterative deformation process. Finally, a spherical wavelet transform is computed to obtain the objects 3D multiresolution model. This paper shows a number of real objects acquired with different techniques, including hand-held 3D digitizers. The paper also gives some examples of how multiresolution representations can be used in tasks such as acquisition noise filtering, mesh simplification and shape labelling.

Surface approximation of 3D objects from irregularly sampled clouds of 3D points using spherical wavelets

This paper presents a technique for computing multiresolution shape models of 3D objects acquired as clouds of 3D points. The procedure is fully automated and is able to process data from any object with a genus equivalent to that of a sphere. An important feature of this method is that it does not impose any restrictions on the input data, which can be provided by any kind of 3D sensor. The method described here starts by computing an intermediate mesh that meets the subdivision connectivity requirement needed to allow the computation of the wavelet transform. The mesh is then adjusted to the 3D input data by means of an iterative deformation process. Finally, a spherical wavelet transform is computed to obtain the objects 3D multiresolution model The paper presents some real examples acquired with a hand-held 3D digitizer.

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.

Neuronize: a tool for building realistic neuronal cell morphologies

This study presents a tool, Neuronize, for building realistic three-dimensional models of neuronal cells from the morphological information extracted through computer-aided tracing applications. Neuronize consists of a set of methods designed to build 3D neural meshes that approximate the cell membrane at different resolution levels, allowing a balance to be reached between the complexity and the quality of the final model. The main contribution of the present study is the proposal of a novel approach to build a realistic and accurate 3D shape of the soma from the incomplete information stored in the digitally traced neuron, which usually consists of a 2D cell body contour. This technique is based on the deformation of an initial shape driven by the position and thickness of the first order dendrites. The addition of a set of spines along the dendrites completes the model, building a final 3D neuronal cell suitable for its visualization in a wide range of 3D environments.

CBIR on grids

From the computational point of view, Content-based Im- age Retrieval systems are potentially expensive and have user response times growing with the ever-increasing sizes of the databases associated to them This paper presents a grid implementation of a Content-based Image Retrieval system that offers a good cost/performance ratio to solve this problem due to their excellent flexibility, scalability and fault tolerance This approach allows a dynamic management of specific data- bases that can be incorporated to or removed from the CBIR system in function of the desired user query Experimental performance results are collected in order to show the feasibility of this solution.

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.