Integration of perceptal grouping and depth

International Conference on Pattern Recognition (ICPR), 2000, Barcelona (España)Different data acquisition methods are tailored at extracting particular characteristics from a scene and by combining their results a more robust scene description can be created. A method to fuse perceptual groupings extracted from color-based segmentation and depth information from stereo using supervised classification is presented. The merging of data from these two acquisition modules allows for a spatially coherent blend of smooth regions and detail in an image. Depth cues are used to limit the area of interest in the scene and to improve perceptual grouping solving subsegmentation and oversegmentation of the original images. The complexity of the algorithm does not exceed that of the individual acquisition modules. The resulting scene description can then be fed to an object recognition modules for scene interpretation.This work was supported by the project 'Active vision systems based in automatic learning for industrial applications' ().Peer Reviewe

A stochastic state estimation approach to simultaneous localization and map building

This monograph covers theoretical aspects of simultaneous localization and map building for mobile robots, such as estimation stability, nonlinear models for the propagation of uncertainties, temporal landmark compatibility, as well as issues pertaining the coupling of control and SLAM. One of the most relevant topics covered in this monograph is the theoretical formalism of partial observability in SLAM. The authors show that the typical approach to SLAM using a Kalman filter results in marginal filter stability, making the final reconstruction estimates dependent on the initial vehicle estimates. However, by anchoring the map to a fixed landmark in the scene, they are able to attain full observability in SLAM, with reduced covariance estimates. This result earned the first author the EURON Georges Giralt Best PhD Award in its fourth edition, and has prompted the SLAM community to think in new ways to approach the mapping problem. For example, by creating local maps anchored on a landmark, or on the robot initial estimate itself, and then using geometric relations to fuse local maps globally. This monograph is appropriate as a text for an introductory estimation-theoretic approach to the SLAM problem, and as a reference book for people who work in mobile robotics research in general.This work was supported by projects: 'Supervised learning of industrial scenes by means of an active vision equipped mobile robot.' (J-00063), 'Integration of robust perception, learning, and navigation systems in mobile robotics' (J-0929).Peer Reviewe

Boosted Random ferns for object detection

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper we introduce the Boosted Random Ferns (BRFs) to rapidly build discriminative classifiers for learning and detecting object categories. At the core of our approach we use standard random ferns, but we introduce four main innovations that let us bring ferns from an instance to a category level, and still retain efficiency. First, we define binary features on the histogram of oriented gradients-domain (as opposed to intensity-), allowing for a better representation of intra-class variability. Second, both the positions where ferns are evaluated within the sliding window, and the location of the binary features for each fern are not chosen completely at random, but instead we use a boosting strategy to pick the most discriminative combination of them. This is further enhanced by our third contribution, that is to adapt the boosting strategy to enable sharing of binary features among different ferns, yielding high recognition rates at a low computational cost. And finally, we show that training can be performed online, for sequentially arriving images. Overall, the resulting classifier can be very efficiently trained, densely evaluated for all image locations in about 0.1 seconds, and provides detection rates similar to competing approaches that require expensive and significantly slower processing times. We demonstrate the effectiveness of our approach by thorough experimentation in publicly available datasets in which we compare against state-of-the-art, and for tasks of both 2D detection and 3D multi-view estimation.Peer ReviewedPostprint (author's final draft

Dynamic object detection fusing LIDAR data and images

We present a method to segment dynamic objects on point clouds using images and 3D laser data. Per-pixel background classes are adapted online as Gaussian Mixtures independently for each sensor. The learned classes are fused labeling pixels/voxels that belong to either the background, or the dynamic objects We pay special attention in the calibration and synchronization modules to reach accuracy in registration and data association. We show results of people segmentation in indoor scenes using a Velodyne sensor at a high frame-rate .Postprint (author’s final draft

Characterization of potato parents for resistance to Phytophthora infestans

El mejoramiento genético de patata (Solanum tuberosum) ha demostrado que, debido a la heterosis, el genoma del grupo andigenum puede mejorar el desempeño de diferentes caracteres del grupo tuberosum. El objetivo de esta investigación fue caracterizar mediante heterosis, progenitores de patata y sus progenies en respuesta a la infección de Phytophthora infestans para identificar genotipos con capacidad de transmitir resistencia. Las progenies se obtuvieron por cruzamiento dialélico entre seis progenitores (cuatro andigenum: Jaspe, Chotañawi, Pollerita y Robusta; dos tuberosum: Libertas e INRA 92T.114.76). La primera generación clonal se obtuvo en la localidad de Lozano (24o6’ S, 65o25’ W, 1350 msnm), Jujuy, Argentina. La segunda generación clonal conformada por quince familias de tubérculos fueron inoculadas con P. infestans. El ensayo se realizó en la Estación Experimental Agropecuaria Balcarce (37o 45’ S, 58o 18’ W, 120 msnm) Buenos Aires, Argentina, y tuvo un diseño en bloques completos aleatorizados con dos repeticiones. Se midió el área bajo la curva del progreso de la enfermedad (AUDPC); en base al análisis de Griffing, se estimaron parámetros de Aptitud Combinatoria General y Específica (ACG y ACE). También se estimaron componentes de varianza, heredabilidad en sentido amplio (H2) y estricto (h2), heterosis media, heterobeltiosis, heterosis específica (Hs) y se definió la estructura heterótica de los cruzamientos sobresalientes. Los resultados obtenidos mostraron que la aptitud combinatoria fue significativa; la razón ACG/ACE indicó acción génica aditiva. El cultivar Robusta fue identificado como el mejor progenitor en virtud de su alto valor de ACG y por participar en un cruzamiento con ACE significativa. En el mismo sentido, la ACE señaló como mejor híbrido a Robusta x Chotañawi. Un tercio de la progenie...Potato (Solanum tuberosum) breeding has shown that, due to heterosis, the genome of the andigenum group can improve the performance of different characters of the tuberosum group. The objective of this work was to characterize potato parents and their progenies by heterosis to identify genotypes with potential for transmitting resistance to the infection of Phytophthora infestans. The progenies were obtained by diallel crossing of six parents (four andigenum: Jaspe, Chotañawi, Pollerita and Robusta; two tuberosum: Libertas and INRA 92T.114.76). The first clonal generation was obtained in the locality of Lozano (24o6’ S, 65o25’ W, 1350 m a.s.l.), Jujuy, Argentina. The second clonal generation comprised fifteen tuber families and was inoculated with P. infestans. The trials were performed in Balcarce Agricultural Experiment Station (37o 45’ S, 58o 18’ W, 120 m a.s.l.), Buenos Aires, Argentina, using a randomized complete block design with two replicates. The Area Under Disease Progress Curve (AUDPC) was recorded; based on the analysis of Griffing, General and Specific Combining Ability (GCA and SCA) was estimated. Variance components, broad-sense (H2) and narrow-sense (h2) heritability, average heterosis, heterobeltiosis, and specific heterosis (Hs) were also estimated; the heterotic structure of the outstanding crosses was defined. Results showed that the combining ability was significant; the GCA/SCA ratio indicated additive gene action. Robusta parent cultivar was identified as best parent based on its high GCA value and for its participation on a cross with significant SCA. The SCA showed that Robusta x Chotañawi was the best hybrid. One third of the progeny expressed favorable additivity to resistance at all heterosis levels. The Hs values showed equivalence with the percent reduction of AUDPC. The heterotic structure found that the additive effects were more important than non-additive effects an

Características clínicas de los pacientes con trauma militar en pie y tobillo, manejados con el fijador externo ilizarov durante el período 2011 - 2012

Análisis descriptivo de las variables sociodemográficas y de las características clínicas de los pacientes. Resultados: Se operaron 10 pacientes, 4 cumplieron criterios de inclusión, edad promedio 25 años, 100% (4) de sexo masculino, 3 heridos por mina antipersonal, 3 fracturas abiertas grado IIIB de Gustilo, con Escala AOFAS de retropié posoperatoria con una media de 67 a los 6 meses (sobre 86)

Estimator stability analysis in SLAM

IFAC Symposium on Intelligent Autonomous Vehicles (IAV), 2004, Lisboa (Portugal)This work presents an analysis of the state estimation error dynamics for a linear system within the Kalman filter based approach to Simultaneous Localization and Map Building. Our objective is to demonstrate that such dynamics is marginally stable. The paper also presents the necessary modifications required in the observation model, in order to guarantee zero mean stable error dynamics. Simulations for a one-dimensional robot and a planar vehicle are presented.This work was supported by the project 'Supervised learning of industrial scenes by means of an active vision equipped mobile robot.' (J-00063).Peer Reviewe

Characterization of potato parents based on combining ability and heterosis for searching resistance to Phytophthora infestans

Controlar efectivamente a Phytophthora infestans, deviene de seleccionar genotipos con capacidad de transmitir resistencia. Con el objeto de caracterizar progenitores de papa en base a aptitud combinatoria y heterosis para resistencia a P. infestans, se cruzaron seis variedades (Libertas, Jaspe, Chotañawi, Pollerita, Robusta e INRA 92T.114.76). Quince familias de tubérculos de segunda generación clonal, obtenidas, fueron inoculadas con P. infestans en Balcarce (Buenos Aires, Argentina) y evaluadas bajo diseño en bloques completos aleatorizados con dos repeticiones. Se midió área bajo la curva del progreso de la enfermedad (AUDPC). Se estimó Aptitud Combinatoria (AC) general y específica, heterosis media, heterobeltiosis, heterosis específica (Hs) y heredabilidad en sentido amplio (H2) y estricto (h2). La AC fue significativa. El progenitor Robusta disminuyó la enfermedad estimada por AUDPC, el valor negativo grande de AC específica señaló mejor híbrido a Robusta x Chotañawi. Un tercio de las cruzas expresaron aditividad en todos los niveles de heterosis. Los valores de Hs manifestaron equivalencia con el porcentaje de disminución del AUDPC. Las heredabilidades (H2=0,63 y h2=0,54) indicaron que la selección por bajo AUDPC puede ser efectiva. El progenitor Robusta y la cruza Robusta x Chotañawi, conformaron los genotipos superiores recomendados para transferir resistencia a P. infestans.The efficient control of Phytopthora infestans results from the selection of genotypes with the capacity of transferring resistance. In order to characterize potato parents based on combining ability and heterosis for their resistance to P. infestans, six parents were crossed (Libertas, Jaspe, Chotañawi, Pollerita, Robusta and INRA 92T.114.76). The 15 tuber families of second clonal generation obtained were inoculated with P. infestans in Balcarce (Buenos Aires, Argentina) and evaluated under randomized complete block design with two replicates. Area Under Disease Progress Curve (AUDPC) was recorded for each genotype; general and specific combining ability, average heterosis, heterobeltiosis, specific heterosis and broad-sense (H2) and narrow (h2) heritability were estimated. Combining ability was significant. The Robusta parent reduced the disease estimated by AUDPC; Robusta x Chotañawi was the best hybrid, as observed by the high negative value of specific combining ability. One third of the crosses expressed significant additive effects for all levels of heterosis. Hs values showed equivalence with the percent reduction of AUDPC. The obtained heritabilities (H2=0.63 and h2=0.54) indicated that selection based on the low AUDPC values can be effective. Robusta parent and Robusta x Chotañawi cross are good genotypes for transmitting resistance to P. infestans.Fil: Andrade, Alberto Juan. Universidad Nacional de JujuyFil: Capezio, Silvia Beatriz.Fil: Huarte, Marcelo Atilio

Stochastic State Estimation for Simultaneous Localization and Map Building in Mobile Robotics

En Cutting Edge Robotics, 223-242. Advanced Robotic Systems Press, 2005.The study of stochastic models for Simultaneous Localization and Map Building (SLAM) in mobile robotics has been an active research topic for over fifteen years. Within the Kalman filter (KF) approach to SLAM, seminal work (Smith and Cheeseman, 1986) suggested that as successive landmark observations take place, the correlation between the estimates of the location of such landmarks in a map grows continuously. This observation was later ratified (Dissanayake et al., 2001) with a proof showing that the estimated map converges monotonically to a relative map with zero uncertainty. They also showed how the absolute accuracy of the map reaches a lower bound defined only by the initial vehicle uncertainty, and proved it for a one-landmark vehicle with no process noise. From an estimation theoretic point of view, we address these results as a consequence of partial observability. We show that error free reconstruction of the map state vector is not possible with typical measurement models, regardless of the vehicle model chosen, and show experimentally that the expected error in state estimation is proportional to the number of landmarks used. Error free reconstruction is only possible once full observability is guaranteed.This work was supported by projects: 'Supervised learning of industrial scenes by means of an active vision equipped mobile robot.' (J-00063), 'Integration of robust perception, learning, and navigation systems in mobile robotics' (J-0929).Peer Reviewe