The flow of baseline estimation using a single omnidirectional camera

Baseline is a distance between two cameras, but we cannot get information from a single camera. Baseline is one of the important parameters to find the depth of objects in stereo image triangulation. The flow of baseline is produced by moving the camera in horizontal axis from its original location. Using baseline estimation, we can determined the depth of an object by using only an omnidirectional camera. This research focus on determining the flow of baseline before calculating the disparity map. To estimate the flow and to tracking the object, we use three and four points in the surface of an object from two different data (panoramic image) that were already chosen. By moving the camera horizontally, we get the tracks of them. The obtained tracks are visually similar. Each track represent the coordinate of each tracking point. Two of four tracks have a graphical representation similar to second order polynomial

Pose Estimation for Omni-directional Cameras using Sinusoid Fitting

We propose a novel pose estimation method for geometric vision of omni-directional cameras. On the basis of the regularity of the pixel movement after camera pose changes, we formulate and prove the sinusoidal relationship between pixels movement and camera motion. We use the improved Fourier-Mellin invariant (iFMI) algorithm to find the motion of pixels, which was shown to be more accurate and robust than the feature-based methods. While iFMI works only on pin-hole model images and estimates 4 parameters (x, y, yaw, scaling), our method works on panoramic images and estimates the full 6 DoF 3D transform, up to an unknown scale factor. For that we fit the motion of the pixels in the panoramic images, as determined by iFMI, to two sinusoidal functions. The offsets, amplitudes and phase-shifts of the two functions then represent the 3D rotation and translation of the camera between the two images. We perform experiments for 3D rotation, which show that our algorithm outperforms the feature-based methods in accuracy and robustness. We leave the more complex 3D translation experiments for future work.Comment: 8 pages, 5 figures, 1 tabl

Ferramenta de análise e simulação computacional de sistema catadióptrico omnidirecional hiperbólico de lobo duplo

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Mecânica, 2012.A cada dia tornam-se mais comuns aplicações de Visão Computacional no cotidiano. Com o intuito de fortalecer este tipo de aplicações, torna-se interessante o estudo de técnicas e métodos que permitam aumentar o campo de visão de câmeras (ferramentas básicas para captura de imagens em sistemas computacionais de visão). O campo de estudo da visão computacional omnidirecional aparece então como uma estratégia promissora para dar vazão a este interesse. Com foco em aumentar a capacidade da câmera em capturar informações do ambiente, a visão omnidirecional levanta uma variedade de técnicas com tal propósito, entre elas a visão omnidirecional catadióptrica, que baseia-se na utilização de espelhos para permitir a captura de imagens com campo de visão de 360º do ambiente. Entre os diferentes perfis de espelhos possíveis de se utilizar junto à câmera, este trabalho foca no uso do espelho convexo hiperbólico de lobo duplo. Este espelho além de possuir a propriedade de centro único de projeção (que minimiza as distorções geométricas das imagens geradas pelo ambiente), permite a captura de duas imagens diferentes da mesma cena, permitindo assim o uso de estereoscopia omnidirecional para cálculo de informações do ambiente. Este trabalho tem como objetivo verificar a influência dos parâmetros de criação do espelho hiperbólico de lobo duplo na reconstrução de cenas simples. Para tal, a simulação computacional de um sistema omnidirecional estéreo catadióptrico baseado em espelho duplo, a partir de imagens panorâmicas cilíndricas, é realizada. Estas imagens servem de base para a realização da estereoscopia omnidirecional. Um sistema computacional denominado de OmniViz foi elaborado para tal tarefa. Ele permite que o usuário personalize os parâmetros de construção do espelho, simula a imagem omnidirecional a partir de uma imagem panorâmica cilíndrica, acentua as características que serão utilizadas (neste caso os cantos dos objetos), realiza a correlação dos pontos e calcula as distâncias destas para o sistema de visão simulado. Além disso um trabalho de análise dos resultados é realizado com a ajuda do MatLab® para se validar a eficiência do sistema apresentado. Esta análise baseia-se no erro associado às alterações dos parâmetros do espelho, em relação ao cálculo das informações do ambiente. Os resultados demonstram que as escolhas corretas de parâmetros do espelho, implicam na capacidade do espelho de gerar imagens que podem facilitar ou dificultar a reconstrução de uma determinada cena. _______________________________________________________________________________________ ABSTRACTEach day computer vision applications become more common in daily life. Aiming at strengthening this type of applications the study of techniques and methods to increase the cameras field of view becomes interesting. The field of omnidirectional computer vision appears as a promising strategy to give vents to this interest. With focus on increasing the camera’s capacity to capture information from an environment, the omnidirectional vision raises a variety of techniques for that purpose, including the catadioptric omnidirectional vision, which is based on the use of mirrors to allow the capture a wide angle image from the environment. Among different profiles of possible mirrors that could be used with the camera, this work focuses on the use of convex hyperbolic double lobed mirror. This mirror also has the single view point property (minimizing geometric images distortions generated by the environment), which allows to capture two different images of the same scene, thus making it possible the use of omnidirectional stereoscopic for calculating environmental information. This work aims to verify of the parameters influence to create the hyperbolic double lobed mirror to allow the scene reconstruction. For this, the simulation of a double lobed catadioptric omnidirectional system from cylindrical panoramic images is performed. These images are basis for performing stereoscopic omnidirectional to calculate the distances between objects corners present in the scene relative the capture system. A software called OmniViz was prepared for such task. It allows the user to customize the mirror design parameters, simulates the omnidirectional image from a cylindrical panoramic image, emphasizes the features that will be used (in this case the objects corners), performs the points correlation and calculates the distances between points and the simulated vision system. Still an analysis is performed with aid of MatLab ® to validate the efficiency of the presented system. This analysis is based on the error associated with the parameter changes of the mirror design, in relation to calculating environmental data. The results demonstrate that the correct choices of the design mirror parameters imply in the mirror ability to generate images that can facilitate or hinder the reconstruction of a particular scene

Enhancing 3D Visual Odometry with Single-Camera Stereo Omnidirectional Systems

We explore low-cost solutions for efficiently improving the 3D pose estimation problem of a single camera moving in an unfamiliar environment. The visual odometry (VO) task -- as it is called when using computer vision to estimate egomotion -- is of particular interest to mobile robots as well as humans with visual impairments. The payload capacity of small robots like micro-aerial vehicles (drones) requires the use of portable perception equipment, which is constrained by size, weight, energy consumption, and processing power. Using a single camera as the passive sensor for the VO task satisfies these requirements, and it motivates the proposed solutions presented in this thesis. To deliver the portability goal with a single off-the-shelf camera, we have taken two approaches: The first one, and the most extensively studied here, revolves around an unorthodox camera-mirrors configuration (catadioptrics) achieving a stereo omnidirectional system (SOS). The second approach relies on expanding the visual features from the scene into higher dimensionalities to track the pose of a conventional camera in a photogrammetric fashion. The first goal has many interdependent challenges, which we address as part of this thesis: SOS design, projection model, adequate calibration procedure, and application to VO. We show several practical advantages for the single-camera SOS due to its complete 360-degree stereo views, that other conventional 3D sensors lack due to their limited field of view. Since our omnidirectional stereo (omnistereo) views are captured by a single camera, a truly instantaneous pair of panoramic images is possible for 3D perception tasks. Finally, we address the VO problem as a direct multichannel tracking approach, which increases the pose estimation accuracy of the baseline method (i.e., using only grayscale or color information) under the photometric error minimization as the heart of the “direct” tracking algorithm. Currently, this solution has been tested on standard monocular cameras, but it could also be applied to an SOS. We believe the challenges that we attempted to solve have not been considered previously with the level of detail needed for successfully performing VO with a single camera as the ultimate goal in both real-life and simulated scenes