Line based camera calibration in machine vision dynamic applications

The problem of dynamic camera calibration considering moving objects in close range environments using straight lines as references is addressed. A mathematical model for the correspondence of a straight line in the object and image spaces is discussed. This model is based on the equivalence between the vector normal to the interpretation plane in the image space and the vector normal to the rotated interpretation plane in the object space. In order to solve the dynamic camera calibration, Kalman Filtering is applied; an iterative process based on the recursive property of the Kalman Filter is defined, using the sequentially estimated camera orientation parameters to feedback the feature extraction process in the image. For the dynamic case, e.g. an image sequence of a moving object, a state prediction and a covariance matrix for the next instant is obtained using the available estimates and the system model. Filtered state estimates can be computed from these predicted estimates using the Kalman Filtering approach and based on the system model parameters with good quality, for each instant of an image sequence. The proposed approach was tested with simulated and real data. Experiments with real data were carried out in a controlled environment, considering a sequence of images of a moving cube in a linear trajectory over a flat surface.

Adaptative techniques for the human faces detection

This paper presents results from an efficient approach to an automatic detection and extraction of human faces from images with any color, texture or objects in background, that consist in find isosceles triangles formed by the eyes and mouth.

A low cost structured light system

The aim of this paper is to present the current development status of a low cost system for surface reconstruction with structured light. The acquisition system is composed of a single off-the-shelf digital camera and a pattern projector. A pattern codification strategy was developed to allow the pattern recognition automatically and a calibration methodology ensures the determination of the direction vector of each pattern. The experiments indicated that an accuracy of 0.5mm in depth could be achieved for typical applications.

Influence of the facial pattern on ANB, AF-BF, and Wits appraisal.

AIM: To assess the correlation between Wits and AF-BF appraisals with the ANB angle, and verify the influence of the facial type on these appraisals. METHODS: Lateral cephalometric radiographs from 118 untreated individuals were separated into 3 groups according to the facial pattern (brachyfacial, mesofacial, and dolichofacial). The radiographs were digitized and submitted to ANB angle and Wits and AF-BF appraisals on computer software. All radiographs were retraced for intraobserver and interobserver error tests. RESULTS: The Student's t test demonstrated no statistically significant differences on the intraobserver's test (P > .05). There were statistically significant differences in the readings of Wits values of the 3 groups and for AF-BF values in the brachyfacial and mesofacial groups (P <.05). The multiple linear regression tests demonstrated high correlation between ANB and AF-BF for the 3 groups (r2, 0.768). The same result was found for ANB and Wits (r2, 0.624). CONCLUSION: Facial pattern does not have an influence on the correlation between ANB and AF-BF nor between ANB and Wits, but it does influence the measurements of ANB, AF-BF, and Wits.

Improving the accuracy of the optimum-path forest supervised classifier for large datasets

In this work, a new approach for supervised pattern recognition is presented which improves the learning algorithm of the Optimum-Path Forest classifier (OPF), centered on detection and elimination of outliers in the training set. Identification of outliers is based on a penalty computed for each sample in the training set from the corresponding number of imputable false positive and false negative classification of samples. This approach enhances the accuracy of OPF while still gaining in classification time, at the expense of a slight increase in training time. © 2010 Springer-Verlag.

A Markov random field model for combining optimum-path forest classifiers using decision graphs and game strategy approach

The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed rules and decision templates are often used. Therefore, the influence and relationship between classifier decisions are often not considered in the combination schemes. In this paper we propose a framework to combine classifiers using a decision graph under a random field model and a game strategy approach to obtain the final decision. The results of combining Optimum-Path Forest (OPF) classifiers using the proposed model are reported, obtaining good performance in experiments using simulated and real data sets. The results encourage the combination of OPF ensembles and the framework to design multiple classifier systems. © 2011 Springer-Verlag.

Estudo de métodos para classificação e localização precisa de padrões usando um sistema de luz estruturada

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Machine vision to identify broiler breeder behavior

Animal behavioral parameters can be used to assess welfare status in commercial broiler breeders. Behavioral parameters can be monitored with a variety of sensing devices, for instance, the use of video cameras allows comprehensive assessment of animal behavioral expressions. Nevertheless, the development of efficient methods and algorithms to continuously identify and differentiate animal behavior patterns is needed. The objective this study was to provide a methodology to identify hen white broiler breeder behavior using combined techniques of image processing and computer vision. These techniques were applied to differentiate body shapes from a sequence of frames as the birds expressed their behaviors. The method was comprised of four stages: (1) identification of body positions and their relationship with typical behaviors. For this stage, the number of frames required to identify each behavior was determined; (2) collection of image samples, with the isolation of the birds that expressed a behavior of interest; (3) image processing and analysis using a filter developed to separate white birds from the dark background; and finally (4) construction and validation of a behavioral classification tree, using the software tool Weka (model 148). The constructed tree was structured in 8 levels and 27 leaves, and it was validated using two modes: the set training mode with an overall rate of success of 96.7%, and the cross validation mode with an overall rate of success of 70.3%. The results presented here confirmed the feasibility of the method developed to identify white broiler breeder behavior for a particular group of study. Nevertheless, more improvements in the method can be made in order to increase the validation overall rate of success. (C) 2013 Elsevier B.V. All rights reserved.

Static Video Summarization through Optimum-Path Forest Clustering

This paper introduces the Optimum-Path Forest (OPF) classifier for static video summarization, being its results comparable to the ones obtained by some state-of-the-art video summarization techniques. The experimental section has been conducted using several image descriptors in two public datasets, followed by an analysis of OPF robustness regarding one ad-hoc parameter. Future works are guided to improve OPF effectiveness on each distinct video category.

Facial Reanimation Utilizing Combined Orthodromic Temporalis Muscle Flap and End-to-Side Cross-Face Nerve Grafts

Individuals with facial paralysis of 6 months or more without evidence of clinical or electromyographic improvement have been successfully reanimated utilizing an orthodromic temporalis transfer in conjunction with end-to-side cross-face nerve grafts. The temporalis muscle insertion is released from the coronoid process of the mandible and sutured to a fascia lata graft that is secured distally to the commissure and paralyzed hemilip. The orthodromic transfer of the temporalis muscle overcomes the concave temporal deformity and zygomatic fullness produced by the turning down of the central third of the muscle (Gillies procedure) while yielding stronger muscle contraction and a more symmetric smile. The muscle flap is combined with cross-face sural nerve grafts utilizing end-to-side neurorrhaphies to import myelinated motor fibers to the paralyzed muscles of facial expression in the midface and perioral region. Cross-face nerve grafting provides the potential for true spontaneous facial motion. We feel that the synergy created by the combination of techniques can perhaps produce a more symmetrical and synchronized smile than either procedure in isolation.Nineteen patients underwent an orthodromic temporalis muscle flap in conjunction with cross-face (buccal-buccal with end-to-side neurorrhaphy) nerve grafts. To evaluate the symmetry of the smile, we measured the length of the two hemilips (normal and affected) using the CorelDRAW X3 software. Measurements were obtained in the pre- and postoperative period and compared for symmetry.There was significant improvement in smile symmetry in 89.5 % of patients.Orthodromic temporalis muscle transfer in conjunction with cross face nerve grafts creates a synergistic effect frequently producing an aesthetic, symmetric smile.This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors at www.spinger.com/00266.

HTS and HTSn: New shape descriptors based on Hough transform statistics

With the widespread proliferation of computers, many human activities entail the use of automatic image analysis. The basic features used for image analysis include color, texture, and shape. In this paper, we propose a new shape description method, called Hough Transform Statistics (HTS), which uses statistics from the Hough space to characterize the shape of objects or regions in digital images. A modified version of this method, called Hough Transform Statistics neighborhood (HTSn), is also presented. Experiments carried out on three popular public image databases showed that the HTS and HTSn descriptors are robust, since they presented precision-recall results much better than several other well-known shape description methods. When compared to Beam Angle Statistics (BAS) method, a shape description method that inspired their development, both the HTS and the HTSn methods presented inferior results regarding the precision-recall criterion, but superior results in the processing time and multiscale separability criteria. The linear complexity of the HTS and the HTSn algorithms, in contrast to BAS, make them more appropriate for shape analysis in high-resolution image retrieval tasks when very large databases are used, which are very common nowadays. (C) 2014 Elsevier Inc. All rights reserved.

Reconhecimento de faces 3D com Kinect

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Effects of diazepam on BOLD activation during the processing of aversive faces

This study aimed to measure, using fMRI, the effect of diazepam on the haemodynamic response to emotional faces. Twelve healthy male volunteers (mean age = 24.83 +/- 3.16 years), were evaluated in a randomized, balanced-order, double-blind, placebo-controlled crossover design. Diazepam (10 mg) or placebo was given 1 h before the neuroimaging acquisition. In a blocked design covert face emotional task, subjects were presented with neutral (A) and aversive (B) (angry or fearful) faces. Participants were also submitted to an explicit emotional face recognition task, and subjective anxiety was evaluated throughout the procedures. Diazepam attenuated the activation of right amygdala and right orbitofrontal cortex and enhanced the activation of right anterior cingulate cortex (ACC) to fearful faces. In contrast, diazepam enhanced the activation of posterior left insula and attenuated the activation of bilateral ACC to angry faces. In the behavioural task, diazepam impaired the recognition of fear in female faces. Under the action of diazepam, volunteers were less anxious at the end of the experimental session. These results suggest that benzodiazepines can differentially modulate brain activation to aversive stimuli, depending on the stimulus features and indicate a role of amygdala and insula in the anxiolytic action of benzodiazepines.

Dynamic texture analysis and segmentation using deterministic partially self-avoiding walks

Dynamic texture is a recent field of investigation that has received growing attention from computer vision community in the last years. These patterns are moving texture in which the concept of selfsimilarity for static textures is extended to the spatiotemporal domain. In this paper, we propose a novel approach for dynamic texture representation, that can be used for both texture analysis and segmentation. In this method, deterministic partially self-avoiding walks are performed in three orthogonal planes of the video in order to combine appearance and motion features. We validate our method on three applications of dynamic texture that present interesting challenges: recognition, clustering and segmentation. Experimental results on these applications indicate that the proposed method improves the dynamic texture representation compared to the state of the art.

Gender classification in large databases

[EN]In this paper, we address the challenge of gender classi - cation using large databases of images with two goals. The rst objective is to evaluate whether the error rate decreases compared to smaller databases. The second goal is to determine if the classi er that provides the best classi cation rate for one database, improves the classi cation results for other databases, that is, the cross-database performance.