Image Registration by Combining Thin-Plate Splines With a 3D Morphable Model

Registering images of a deforming surface is a well-studied problem. It is common practice to describe the image deformation fields with Thin-Plate Splines. This has the advantage to involve small numbers of parameters, but has the drawback that the 3D surface is not explicitly reconstructed. We propose an image deformation model combining Thin-Plate Splines with 3D entities – a 3D control mesh and a camera – overcoming the above mentioned drawback. An original solution to the non-rigid image registration problem using this model is proposed and demonstrated on simulated and real data

Real-time human detection in urban scenes: Local descriptors and classifiers selection with adaboost-like algorithms

This paper deals with the study of various implementations of the AdaBoost algorithm in order to address the issue of real-time pedestrian detection in images. We use gradient-based local descriptors and we combine them to form strong classifiers organized in a cascaded detector. We compare the original AdaBoost algorithm with two other boosting algorithms we developed. One optimizes the use of each selected descriptor to minimize the operations done in the image (method 1), leading to an acceleration of the detection process without any loss in detection performances. The second algorithm (method 2) improves the selection of the descriptors by associating to each of them a more powerful weak-learner – a decision tree built from the components of the whole descriptor – and by evaluating them locally. We compare the results of these three learning algorithms on a reference database of color images and we then introduce our preliminary results on the adaptation of this detector on infrared vision. Our methods give better detection rates and faster processing than the original boosting algorithm and also provide interesting results for further studies. 1

3D Reconstruction of Complex Structures with Bundle Adjustment: an Incremental Approach

This paper introduces an incremental method for "Structure From Motion" of complex scenes from a video sequence. More precisely, we estimate the 3D positions of the viewed points in images and the camera positions and orientations through the sequence. The method can be seen as a fast but accurate alternative to classical reconstruction methods that use bundle adjustment, and that can become slow and computation time expensive for very long scenes. Our results are compared to the reconstruction obtained by the classical hierarchical bundle adjustment method. They have also been successfully used as a reference sequence for the vision based localization of an autonomous mobile robot

Détection et localisation d'objets stationnaires par une paire de caméras PTZ

Session "Articles"National audienceDans ce papier, nous proposons une approche originale pour détecter et localiser des objets stationnaires sur une scène étendue en exploitant une paire de caméras PTZ. Nous proposons deux contributions principales. Tout d'abord, nous présentons une méthode de détection et de segmentation d'objets stationnaires. Celle-ci est basée sur la réidentification de descripteurs de l'avant-plan et une segmentation de ces blobs en objets à l'aide de champs de Markov. La seconde contribution concerne la mise en correspondance entre les deux PTZ des silhouettes d'objets détectées dans chaque image

Méthode d'apprentissage pour la classification à partir d'exemples positifs

National audienceCet article présente une méthode d'apprentissage générique et non supervisée à partir d'une seule base d'exemple positif, pour la classification. Le système est formalisé dans un cadre probabiliste. Nous proposons une méthode originale pour approximer la densité de probabilité de la fonction de vraisemblance correspondant aux évènements dit normaux, en utilisant un modèle parcimonieux basé sur des fonctions noyaux. Ce modèle présente l'avantage des méthodes non-paramétriques tout en limitant le coût algorithmique souvent important qui leur est lié. La classification est ensuite effectuée à partir de cette approximation grâce à une notion de confiance. La méthode sera comparée à celle des One Class SVM et testée dans le cas de la détection d'événements rares liés au trafic routier

Estimation of genetic parameters, phenotypic, genotypic and environmental correlations on Barley (Hordeum Vulgare L.) grown under irrigation conditions in the Brazilian Savannah.

The purpose of the present study was to estimate the heritability of traits through phenotypic, genetic and environmental parameters related to the production components and agro-morphological characters: plant height (PHt), days to heading, lodging, grain yield (YLD), thousand kernels weight (TKW), protein content, and commercial classification of grains (CLASS) of an elite collection of 39 barley genotypes grown under irrigated conditions in the savannah of Central Brazil. The experiment was planted under irrigation on May 2009 at Embrapa Cerrados, Federal District, Brazil. A complete randomized block design with four replicates was used. Genetic variability was observed among the tested genotypes. The genotypic correlations (in absolute values) found for all traits were greater than their corresponding phenotypic and environmental correlations. A significant influence of genetic factors on trait expression was observed. It could be concluded that the phenotypic expression is decreased depending on the environmental conditions. The greatest magnitudes for the genotypic and phenotypic correlations were found for TKW and CLASS. Trait YLD was positively correlated to PHt in terms of genotypic and phenotypic correlation. The selection accuracy was rated high for all traits. The high magnitudes found in the estimation of broad sense heritability indicated the existence of genetic variability, showing the possibility of obtaining genetic gains through the selection for all characters

Faktor-faktor Yang Mempengaruhi Kualitas Kinerja Pegawai Kantor Pertanahan Di Kabupaten Rote Ndao

The aim of this research is to analyzes determinant factors (input) and determinant factor (process) to employee working quality (output) in Land Agency in Rote Ndao regency. There are 6 variables used in this research with 6 independent variables and one dependent variable. 6 dependent variables consist of human resources, budget, facility, infrastructure, bureaucracy efficiency, and labor discipline; independent variable is working quality. Population in this research are 30 employees from Land Agency in Rote Ndao regency. Data analysis used in this research is Spearman's correlation analysis method. This research concludes that the six independet variables have significant influnce toward the dependent variable partially and simultaneously

Caracterização agronômica de acessos de cevada de alta produtividade sob irrigação no Cerrado

O objetivo deste trabalho foi estimar parâmetros genéticos, fenotípicos e ambientais de 113 acessos de cevada (Hordeum vulgare), previamente selecionados com base em alta produtividade, em sistema de produção irrigado no Cerrado, para uso em programas de melhoramento no Brasil. O experimento foi realizado em 2013, em dois locais no Distrito Federal, tendo-se utilizado o delineamento experimental de blocos ao acaso, com três repetições. Avaliaram-se as características: rendimento de grãos, classificação comercial de primeira, peso de mil grãos, altura de plantas, acamamento e dias para espigamento. Foram observadas diferenças significativas entre ambientes e acessos para todas as características avaliadas, além de interação genótipo x ambiente. Os acessos MCU 3832 PI 402310, MCU 3484 PI 401962, CI 08053 Custer, MCU 3634 PI 402112 e MCU 3816 PI 402294 destacaram-se em relação ao rendimento de grãos e à classificação comercial de primeira. É possível obter altos ganhos de seleção com altos valores de herdabilidade. No entanto, a seleção indireta não é recomendada nas condições experimentais, em razão das baixas correlações genotípicas e fenotípicas obtidas. Também é possível a seleção simultânea de acessos de cevada com alto rendimento e ciclo de espigamento precoce, fator decisivo no processo de escolha de genótipos para futuros experimentos. Os acessos colombianos são os mais adaptados às condições de Cerrado.The objective of this work was to estimate the genetic, phenotypic, and environmental parameters of 113 barley accessions (Hordeum vulgare), previously selected based on high yield, in an irrigated production system in the Cerrado (Brazilian savanna), for use in breeding programs in Brazil. The experiment was conducted in 2013 at two sites in the Federal District, using a randomized complete block design with three replicates. The evaluated traits were: grain yield, kernel plumpness, thousand grain weight, plant height, lodging, and days to heading. Significant differences were observed between environment and accessions for all studied traits, as well as genotype x environment interaction. The MCU 3832 PI 402310, MCU 3484 PI 401962, CI 08053 Custer, MCU 3634 PI 402112, and MCU 3816 PI 402294 accessions stood out regarding grain yield and kernel plumpness. It is possible to obtain high selection gains with high heritability values. However, indirect selection is not recommended in the experimental conditions due to the low genotypic and phenotypic correlations obtained. It is also possible to select barley accessions with high yield and early heading date simultaneously, an important factor in the genotype selection process for future experiments. The accessions from Colombia are the most adapted to the Cerrado conditions