Odometria visual baseada em técnicas de structure from motion

Visual Odometry is the process that estimates camera position and orientation based solely on images and in features (projections of visual landmarks present in the scene) extraced from them. With the increasing advance of Computer Vision algorithms and computer processing power, the subarea known as Structure from Motion (SFM) started to supply mathematical tools composing localization systems for robotics and Augmented Reality applications, in contrast with its initial purpose of being used in inherently offline solutions aiming 3D reconstruction and image based modelling. In that way, this work proposes a pipeline to obtain relative position featuring a previously calibrated camera as positional sensor and based entirely on models and algorithms from SFM. Techniques usually applied in camera localization systems such as Kalman filters and particle filters are not used, making unnecessary additional information like probabilistic models for camera state transition. Experiments assessing both 3D reconstruction quality and camera position estimated by the system were performed, in which image sequences captured in reallistic scenarios were processed and compared to localization data gathered from a mobile robotic platform

Acelerando algoritmos de baixo nível em visão robótica com hardware reconfigurável

A challenge that remains in the robotics field is how to make a robot to react in real time to visual stimulus. Traditional computer vision algorithms used to overcome this problem are still very expensive taking too long when using common computer processors. Very simple algorithms like image filtering or even mathematical morphology operations may take too long. Researchers have implemented image processing algorithms in high parallelism hardware devices in order to cut down the time spent in the algorithms processing, with good results. By using hardware implemented image processing techniques and a platform oriented system that uses the Nios II Processor we propose an approach that uses the hardware processing and event based programming to simplify the vision based systems while at the same time accelerating some parts of the used algorithms

Fractal analysis of leaf-texture properties as a tool for taxonomic and identification purposes: a case study with species from Neotropical Melastomataceae (Miconieae tribe)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Image processing algorithm for the identification of Martian dust devil tracks in MOC and HiRISE images

This paper presents a method for automatic identification of dust devils tracks in MOC NA and HiRISE images of Mars. The method is based on Mathematical Morphology and is able to successfully process those images despite their difference in spatial resolution or size of the scene. A dataset of 200 images from the surface of Mars representative of the diversity of those track features was considered for developing, testing and evaluating our method, confronting the outputs with reference images made manually. Analysis showed a mean accuracy of about 92%. We also give some examples on how to use the results to get information about dust devils, namelly mean width, main direction of movement and coverage per scene. (c) 2012 Elsevier Ltd. All rights reserved.

Diferenças funcionais das regiões hipocampais na formação da memória do tipo o quê", "quando" e "onde" em ratos

Episodic memory refers to the recollection of what, where and when a specific event occurred. Hippocampus is a key structure in this type of memory. Computational models suggest that the dentate gyrus (DG) and the CA3 hippocampal subregions are involved in pattern separation and the rapid acquisition of episodic memories, while CA1 is involved in memory consolidation. However there are few studies with animal models that access simultaneously the aspects ‗what-where-when . Recently, an object recognition episodic-like memory task in rodents was proposed. This task consists of two sample trials and a test phase. In sample trial one, the rat is exposed to four copies of an object. In sample trial two, one hour later, the rat is exposed to four copies of a different object. In the test phase, 1 h later, two copies of each of the objects previously used are presented. One copy of the object used in sample trial one is located in a different place, and therefore it is expected to be the most explored object.However, the short retention delay of the task narrows its applications. This study verifies if this task can be evoked after 24h and whether the pharmacological inactivation of the DG/CA3 and CA1 subregions could differentially impair the acquisition of the task described. Validation of the task with a longer interval (24h) was accomplished (animals showed spatiotemporal object discrimination and scopolamine (1 mg/kg, ip) injected pos-training impaired performance). Afterwards, the GABA agonist muscimol, (0,250 μg/μl; volume = 0,5 μl) or saline were injected in the hippocampal subregions fifteen minutes before training. Pre-training inactivation of the DG/CA3 subregions impaired the spatial discrimination of the objects (‗where ), while the temporal discrimination (‗when ) was preserved. Rats treated with muscimol in the CA1 subregion explored all the objects equally well, irrespective of place or presentation time. Our results corroborate the computational models that postulate a role for DG/CA3 in spatial pattern separation, and a role for CA1 in the consolidation process of different mnemonic episodes

Efeitos dos esteroides anabólicos androgênicos sobre funções cognitivas de ratos

The use and the demand for substances that enhance masculinity, strength and sexual power are not novel. Over the years, this search has assisted the research directions in this area, leading to the discovery of the primary male sex hormone testosterone in 1935. Since then, numerous testosterone analogue compounds were synthesized, which are generically called Anabolic Androgenic Steroids (AAS). The AAS were produced for therapeutic purposes, but an increase in the use of these compounds for other purposes occurred over time. Initially they were used mainly to improve performance in athletes. However, recent studies have shown that the use of AAS by non-athletes with aesthetical purposes have been increasing as well. The abuse of AAS with non-clinical purposes can promote a number of physiological alterations, such as heart, liver, respiratory and psychological problems such as changes in mood, levels of anxiety and aggression. Exposure to supraphysiological doses of AAS is associated with behavioral changes, however, little is known about the effects of AAS on cognitive functions. In this work, we aimed to mimic the AAS abuse in humans with intramuscular administration of a supraphysiological dose of testosterone propionate (TP) in rats. We investigated the effects of this treatment on different aspects of cognitive function, specifically learning, memory and anxiety. Adult male Wistar rats were tested in the spontaneous alternation, novel object recognition and plus-maze discriminative avoidance tasks. The control group received intramuscular injections of vegetable oil (vehicle), and the TP group received injections of TP (10 mg/kg, i.m.). The injections were administered for 40 days, with intervals of 48 hours (chronic treatment) or in a single injection (acute treatment). In addition to the behavioral assessments, we performed biochemical analyzes as indicators of the endocrine effects of the treatment. Our results show that chronic treatment with a supraphysiological dose of TP caused memory impairments in the novel object recognition and the discriminative avoidance tasks. The spatial working memory (evaluated by spontaneous alternation task) was not affected. Also, we did not observe changes in anxiety levels. Regarding the biochemical parameters, chronic treatment increased serum levels of glutamicpyruvic transaminase, an indicator of hepatic and pancreatic lesions (as those observed after chronic use of these substances in humans). On the other hand, acute treatment with PT did not promote significant changes in any of these parameters when compared to the control group. In summary, we conclude that chronic treatment with a supraphysiological dose of testosterone propionate produces memory deficits in novel object recognition and retrieval of the discriminative avoidance task in adult male rats

Déficits de memória induzidos por baixas doses de reserpina em ratos: possível relação com prejuízos no processamento emocional na Doença de Parkinson

We have recently verified that the monoamine depleting drug reserpine at doses that do not modify motor function - impairs memory in a rodent model of aversive discrimination. In this study, the effects of reserpine (0.1-0.5 mg/kg) on the performance of rats in object recognition, spatial working memory (spontaneous alternation) and emotional memory (contextual freezing conditioning) tasks were investigated. While object recognition and spontaneous alternation behavior were not affected by reserpine treatment, contextual fear conditioning was impaired. Together with previous studies, these results suggest that mild monoamine depletion would preferentially induce deficits in tasks involved with emotional contexts. Possible relationships with cognitive and emotional processing deficits in Parkinson disease are discussed

Alterações do ciclo sono-vigília moduladas por Dopamina e suas consequências Mnemônicas

Neuroscience is on a rise of discoveries. Its wide interdisciplinary approach facilitates a more complex understanding of the brain, covering various areas in depth. However, many phenomena that fascinate human kind are far from being fully elucidated, such as the formation of memories and sleep. In this study we investigated the role of the dopaminergic system in the process of memory consolidation and modulation of the phases of sleep-wake cycle. We used two groups of animals: wildtype mice and hiperdopaminergic mice, heterozygous for the gene encoding the dopamine transporter protein. We observed in wild-type mice that the partial blockade of the D2 dopamine receptor by the drug haloperidol caused deficits in memory consolidation for object recognition, as well as a significant reduction in the duration of rapid eye movement sleep (REM). We also found a mnemonic deficit without pharmacological intervention in hiperdopaminergic animals; this deficit was reversed with haloperidol. The results suggest that dopamine plays a key role in memory consolidation for object recognition. The data also support a functional relationship between the dopaminergic system and the modulation of REM sleep

Melhorando a estimação de pose com o RANSAC preemptivo generalizado e múltiplos geradores de hipóteses

The camera motion estimation represents one of the fundamental problems in Computer Vision and it may be solved by several methods. Preemptive RANSAC is one of them, which in spite of its robustness and speed possesses a lack of flexibility related to the requirements of applications and hardware platforms using it. In this work, we propose an improvement to the structure of Preemptive RANSAC in order to overcome such limitations and make it feasible to execute on devices with heterogeneous resources (specially low budget systems) under tighter time and accuracy constraints. We derived a function called BRUMA from Preemptive RANSAC, which is able to generalize several preemption schemes, allowing previously fixed parameters (block size and elimination factor) to be changed according the applications constraints. We also propose the Generalized Preemptive RANSAC method, which allows to determine the maximum number of hipotheses an algorithm may generate. The experiments performed show the superiority of our method in the expected scenarios. Moreover, additional experiments show that the multimethod hypotheses generation achieved more robust results related to the variability in the set of evaluated motion directions

Utilizando mapas de conectividade fuzzy no desenvolvimento de algoritmos reparadores de imagens binárias 3D

A 3D binary image is considered well-composed if, and only if, the union of the faces shared by the foreground and background voxels of the image is a surface in R3. Wellcomposed images have some desirable topological properties, which allow us to simplify and optimize algorithms that are widely used in computer graphics, computer vision and image processing. These advantages have fostered the development of algorithms to repair bi-dimensional (2D) and three-dimensional (3D) images that are not well-composed. These algorithms are known as repairing algorithms. In this dissertation, we propose two repairing algorithms, one randomized and one deterministic. Both algorithms are capable of making topological repairs in 3D binary images, producing well-composed images similar to the original images. The key idea behind both algorithms is to iteratively change the assigned color of some points in the input image from 0 (background)to 1 (foreground) until the image becomes well-composed. The points whose colors are changed by the algorithms are chosen according to their values in the fuzzy connectivity map resulting from the image segmentation process. The use of the fuzzy connectivity map ensures that a subset of points chosen by the algorithm at any given iteration is the one with the least affinity with the background among all possible choices

Petroleum well drilling monitoring through cutting image analysis and artificial intelligence techniques

Petroleum well drilling monitoring has become an important tool for detecting and preventing problems during the well drilling process. In this paper, we propose to assist the drilling process by analyzing the cutting images at the vibrating shake shaker, in which different concentrations of cuttings can indicate possible problems, such as the collapse of the well borehole walls. In such a way, we present here an innovative computer vision system composed by a real time cutting volume estimator addressed by support vector regression. As far we know, we are the first to propose the petroleum well drilling monitoring by cutting image analysis. We also applied a collection of supervised classifiers for cutting volume classification. (C) 2010 Elsevier Ltd. All rights reserved.

Aprendizado não-supervisionado em redes neurais pulsadas de base radial: um estudo da capacidade de agrupamento para a classificação de pixels

Redes neurais pulsadas - redes que utilizam uma codificação temporal da informação - têm despontado como uma promissora abordagem dentro do paradigma conexionista, emergente da ciência cognitiva. Um desses novos modelos é a rede neural pulsada com função de base radial, que é capaz de armazenar informação nos tempos de atraso axonais dos neurônios. Um algoritmo de aprendizado foi aplicado com sucesso nesta rede pulsada, que se mostrou capaz de mapear uma seqüência de pulsos de entrada em uma seqüência de pulsos de saída. Mais recentemente, um método baseado no uso de campos receptivos gaussianos foi proposto para codificar dados constantes em uma seqüência de pulsos temporais. Este método tornou possível a essa rede lidar com dados computacionais. O processo de aprendizado desta nova rede não se encontra plenamente compreendido e investigações mais profundas são necessárias para situar este modelo dentro do contexto do aprendizado de máquinas e também para estabelecer as habilidades e limitações desta rede. Este trabalho apresenta uma investigação desse novo classificador e um estudo de sua capacidade de agrupar dados em três dimensões, particularmente procurando estabelecer seus domínios de aplicação e horizontes no campo da visão computacional.

Extração de feições rodoviárias em imagens digitais: Metodologias desenvolvidas pelo GP-F&VC

Several kinds of research in road extraction have been carried out in the last 6 years by the Photogrammetry and Computer Vision Research Group (GPF&VC - Grupo de Pesquisa em Fotogrametria e Visão Computacional). Several semi-automatic road extraction methodologies have been developed, including sequential and optimizatin techniques. The GP-F&VC has also been developing fully automatic methodologies for road extraction. This paper presents an overview of the GP-F&VC research in road extraction from digital images, along with examples of results obtained by the developed methodologies.

Um estudo sobre o osu do modelo de cor RGB no proceso de correspondência por correlação

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)