Flavio de Barros Vidal

A dynamic approach for approximate pairwise alignment based on 4-points congruence sets of 3D points

We present a method for approximate 3D point sets alignment to register surfaces with varying degrees of overlap. The approach is based on a novel technique to extract dynamically the sets of coplanar 4-points from a 3D point set which are approximately congruent. The choice of bases from one 3D set to be matched to the others for possible registration is done automatically, and it is refined dynamically by controlling the width of the bases against the degree of overlap to be achieved at each iteration. Besides being an automatic way to perform the alignment, our method is a way to optimize the 4-points bases selection since it converges fast to appropriate bases as they are available. We show and compare reconstruction results using publicly available 3D scan data.

Window-Matching Techniques with Kalman Filtering for an Improved Object Visual Tracking

This paper describes the development and application of an algorithm for object visual tracking from a sequence of images. The algorithm is based on window-matching techniques using the sum of squared differences (SSD) as a distance-similarity measure, but adding stochastic filtering. The algorithm is then applied for tracking: a vehicle on an urban environment; two people meeting and walking together; a ball on a ping-pong game. It is concluded that incorporating the Kalman filtering greatly improves the tracking performance.

Genetic Algorithms and Game Theory for Airport Departure Decision Making: GeDMAN and CoDMAN

Departure Management is responsible for creating a departure sequence of flights and for deciding which aircraft will takeoff firstly in scenarios of cancellation or delay. In many cases, this activity depends only on the experience of air traffic controllers who will empirically decide the departure sequence. This work presents two computational models to address the departure sequencing problem in airports according to Collaborative Decision Making. The first model is GeDMAN, a departure management system that uses Genetic Algorithm. The second one named as CoDMAN is based on the negotiation among the agents (aircraft) in a dynamic scenario using Game Theory. Both approaches are tested with real flight data from Brasilia International Airport. The simulation results show that the developed systems have the capability to manage the departure sequence automatically and reduce the total flight delay efficiently.

A proposal for human action classification based on motion analysis and artificial neural networks

This paper describes the development and application of a method for human action recognition from motion analysis in a sequence of images using an artificial neural network. The proposed method is based on two stages: Computer Vision and Computational Intelligence. The Computer Vision stage is a combination of two motion analysis techniques: Histogram of Oriented Optical Flow and Object Contour Analysis. For the Computational Intelligence stage we use a Self-Organizing Map (SOM) optimized through Learning Vector Quantization (LVQ). The approach is then applied for classification of human actions in many real situations. Testing against a database with different kinds of human actions, we show the usefulness and robustness of this method, comparing it to other proposals in the literature.

Handwritten Text Verification on Mobile Devices

In this work we propose an online verification system for both signature and isolated cursive words. The proposed system is designed to be used in a mobile device with limited computational capability. In the proposed scenario it is assumed that the user will use either his fingertip or a passive pen, therefore no azimuth or inclination information is available. Isolated words have certain desirable traits that can be more useful on a mobile device. Different isolated words can be used to verify the user in different applications, combining a knowledge-based security systems (i.e. passwords) with a behavioral biometric verification system. The proposed technique can achieve 4:39% of equal error rate for signatures and 6:5% for isolated words.

Photoanthropometric face iridial proportions for age estimation: An investigation using features selected via a joint mutual information criterion

Age assessment from images is of high interest in the forensic community because of the necessity to establish formal protocols to identify child pornography, child missing and abuses where visual evidences are the mostly admissible. Recently, photoanthropometric methods have been found useful for age estimation correlating facial proportions in image databases with samples of some age groups. Notwithstanding the advances, newer facial features and further analysis are needed to improve accuracy and establish larger applicability. In this investigation, frontal images of 1000 individuals (500 females, 500 males), equally distributed in five age groups (6, 10, 14, 18, 22 years old) were used in a 10 fold cross-validated experiment for three age thresholds classifications (<10, <14, <18 years old). A set of novel 40 features, based on a relation between landmark distances and the iris diameter, is proposed and joint mutual information is used to select the most relevant and complementary features for the classification task. In a civil image identification database with diverse ancestry, receiver operating characteristic (ROC) curves were plotted to verify accuracy, and the resultant AUCs achieved 0.971, 0.969, and 0.903 for the age classifications (<10, <14, <18 years old), respectively. These results add support to continuing research in age assessment from images using the metric approach. Still, larger samples are necessary to evaluate reliability in extensive conditions.

Agent-based framework to individual tracking in unconstrained environments

A framework to detect, identify and track individuals is proposed.Agents communication language complies with FIPA standards using cloud storage.Manager, face detector and face tracker agents interact by contract net protocol.Face detection uses Scale Invariant Feature Transform/Speeded Up Robust Features.The proposed framework tracks individuals in unconstrained environments. Agents with intelligent perceptual capabilities are considered state-of-the-art in advanced intelligent systems. In addition, a multiagent system is considered an enabling technology for applications that rely on distributed and parallel processing, including data, information and knowledge in complex computing environments. With the aim of creating advanced intelligent systems with visual perception, this paper presents an agent-based framework to individual tracking in unconstrained environments. The framework has three types of agents that interact using the Contract Net Protocol. The face detector and tracker agents perform fully automatic single-sample face recognition using the Viola-Jones and the Scale Invariant Feature Transform/Speeded Up Robust Features algorithms. The experimental results show that the framework adequately recognizes and tracks individuals in unconstrained environments, indicating the path the individuals have taken and the time they spent in the field of view of the surveillance agents. Some of the open source framework advantages are the distribution in heterogeneous infrastructures, the expansion with new agents using different face recognition algorithms (e.g., Eigenfaces), and the individual tracking logs that can be used in different ways, e.g., improve security in surveillance areas such as automated teller machines, self-paying kiosks, movie box offices, and malls.

A parallel hierarchical finite state machine approach to UAV control for search and rescue tasks

The process of developing a system for an Unnamed Aerial Vehicle (UAV) control is a complex task that we should be able to implement a set of elaborated algorithms with specific features as fast response for non-linear inputs, fault tolerance and easy maneuvering procedures. These features define the reachability and quality of the UAV overall control system. In this position paper, we propose a solution for the UAV control process using a Parallel Hierarchical Finite State Machine (PHFSM) that results in a high level system including all features required by an complex UAV control to search and rescue tasks. Following in this approach we can achieve many improvements than other usual implementations. Initials simulation experiments, using data from a simple UAV model, indicate in direction that many issues can be solved by this approach.

Mechanical engineering, computer science and art in interdisciplinary project-based learning projects:

This article describes the approach to promote project-based learning and interdisciplinarity within established engineering undergraduate programs at the University of Brasilia. The implementation process and some representative projects developed are presented, as well, as a discussion about the role of interdisciplinarity in transferable skills acquisition and their many benefits for all students from undergraduate courses involved.

A Bio-inspired Apodal and Modular Robot

Reconfigurable modular robotics is based on the use of autonomous units that can be attached in many ways to exert different kinds of functions. The main idea consists on the robots capacity to adapt to unexpected environmental circumstances and execute its mission. The current works goal is the adaptation of the mechanical system for the apodal movement, based on bio-inspired configuration of a snake for search and rescue situations on debris. Some aspects of the movement are described, followed by the definition and development of the robots structure, aiming for low cost production and easy replacement of the modules. Simulations and experimental tests were conducted to evaluate the robots performance.