Today, 3D models of cities are created from aerial images using a camera rig. Images, together with sensor data from the flights, are stored for further processing when building 3D models. However, there is a market demand for a more mobile solution of satisfactory quality. If the camera position can be calculated for each image, there is an existing algorithm available for the creation of 3D models. This master thesis project aims to investigate whether the iPhone 4 offers good enough image and sensor data quality from which 3D models can be created. Calculations on movements and rotations from sensor data forms the foundation of the image processing, and should refine the camera position estimations. The 3D models are built only from image processing since sensor data cannot be used due to poor data accuracy. Because of that, the scaling of the 3D models are unknown and a measurement is needed on the real objects to make scaling possible. Compared to a test algorithm that calculates 3D models from only images, already available at the SBD’s system, the quality of the 3D model in this master thesis project is almost the same or, in some respects, even better when compared with the human eye.

The field of autonomous vehicle navigation and localization is a highly active research topic. The aim of this thesis is to evaluate the feasibility to use outdoor visual navigation in a semi-structured environment. The goal is to develop a visual navigation system for an autonomous golf ball collection vehicle operating on driving ranges. The image feature extractors SIFT and PCA-SIFT was evaluated on an image database consisting of images acquired from 19 outdoor locations over a period of several weeks to allow different environmental conditions. The results from these tests show that SIFT-type feature extractors are able to find and match image features with high accuracy. The results also show that this can be improved further by a combination of a lower nearest neighbour threshold and an outlier rejection method to allow more matches and a higher ratio of correct matches. Outliers were found and rejected by fitting the data to a homography model with the RANSAC robust estimator algorithm. A simulator was developed to evaluate the suggested system with respect to pixel noise from illumination changes, weather and feature position accuracy as well as the distance to features, path shapes and the visual servoing target image (milestone) interval. The system was evaluated on a total of 3 paths, 40 test combinations and 137km driven. The results show that with the relatively simple visual servoing navigation system it is possible to use mono-vision as a sole sensor and navigate semi-structured outdoor environments such as driving ranges.

In this thesis, we present an algorithm for vision based detection of moving objects observed by IR sensors on a moving platform. In addition we analyze the performance of different approaches in each step of the algorithm. The proposed algorithm is composed of preprocessing, feature detection, feature matching, homography estimation and difference image analysis steps. First, a global motion estimation based on planar homography model is performed in order to compensate the motion of the sensor and moving platform where the sensors are located. Then, moving objects are identified on difference images of consecutive video frames with global motion suppression. Performance of the proposed algorithm is shown on different IR image sequences.

Au cours de ces dernières décennies, le développement de Systèmes Mobiles de Cartographie, soutenu par un progrès technologique important, est devenu plus apparent. Il a été stimulé par le besoin grandissant de collecte d'informations géographiques précises sur l'environnement. Nous considérons, au sein de cette thèse, des solutions pour l'acquisition des nuages de points mobiles de qualité topographique (précision centimétrique). Il s'agit, dans cette tâche, de mettre au point des méthodes de qualification des données, et d'en améliorer sur les erreurs systématiques par des techniques d'étalonnage et de recalage adéquates.Nous décrivons une démarche innovante d'évaluation de l'exactitude et/ou de la précision des relevés laser mobiles. Celle-ci repose sur l'extraction et la comparaison des entités linéaires de la scène urbaine. La distance moyenne calculée entre les segments appariés, étant la distance modifiée de Hausdorff, sert à noter les nuages par rapport à des références existantes. Pour l'extraction des arêtes, nous proposons une méthode de détection d'intersections entre segments plans retrouvés via un algorithme de RANSAC enrichi d'une analyse de composantes connexes. Nous envisageons également une démarche de correction de relevés laser mobiles à travers un recalage rigide fondé, lui aussi, sur les éléments linéaires. Enfin, nous étudions la pertinence des segments pour en déduire les paramètres de l'étalonnage extrinsèque du système mobile. Nous testons nos méthodes sur des données simulées et des données réelles acquises dans le cadre du projet TerraMobilita.

abstract: There is a growing interest in the creation of three-dimensional (3D) images and videos due to the growing demand for 3D visual media in commercial markets. A possible solution to produce 3D media files is to convert existing 2D images and videos to 3D. The 2D to 3D conversion methods that estimate the depth map from 2D scenes for 3D reconstruction present an efficient approach to save on the cost of the coding, transmission and storage of 3D visual media in practical applications. Various 2D to 3D conversion methods based on depth maps have been developed using existing image and video processing techniques. The depth maps can be estimated either from a single 2D view or from multiple 2D views. This thesis presents a MATLAB-based 2D to 3D conversion system from multiple views based on the computation of a sparse depth map. The 2D to 3D conversion system is able to deal with the multiple views obtained from uncalibrated hand-held cameras without knowledge of the prior camera parameters or scene geometry. The implemented system consists of techniques for image feature detection and registration, two-view geometry estimation, projective 3D scene reconstruction and metric upgrade to reconstruct the 3D structures by means of a metric transformation. The implemented 2D to 3D conversion system is tested using different multi-view image sets. The obtained experimental results of reconstructed sparse depth maps of feature points in 3D scenes provide relative depth information of the objects. Sample ground-truth depth data points are used to calculate a scale factor in order to estimate the true depth by scaling the obtained relative depth information using the estimated scale factor. It was found out that the obtained reconstructed depth map is consistent with the ground-truth depth data. / Dissertation/Thesis / M.S. Electrical Engineering 2010

Submitted by ANDRÉ CACERES CARRILHO null (carrilho.acc@gmail.com) on 2016-04-01T02:33:57Z No. of bitstreams: 1 d_carrilho_ac.pdf: 6862099 bytes, checksum: fa858752c5f46a9fc8acf83fee1ed2cc (MD5) / Approved for entry into archive by Ana Paula Grisoto (grisotoana@reitoria.unesp.br) on 2016-04-05T13:36:03Z (GMT) No. of bitstreams: 1 carrilho_ac_me_prud.pdf: 6862099 bytes, checksum: fa858752c5f46a9fc8acf83fee1ed2cc (MD5) / Made available in DSpace on 2016-04-05T13:36:03Z (GMT). No. of bitstreams: 1 carrilho_ac_me_prud.pdf: 6862099 bytes, checksum: fa858752c5f46a9fc8acf83fee1ed2cc (MD5) Previous issue date: 2016-02-16 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / As nuvens de pontos provindas de Sistemas de Varredura a LASER (Light Amplification by Stimulated Emission of Radiation) Aerotransportados (SVLA) representam a superfície com um grande detalhamento, sendo registrada a vegetação e as feições antrópicas, como edificações e rodovias, por exemplo. A automação da tarefa de classificação da nuvem de pontos é importante para a redução de custos em aplicações práticas relacionadas a atividades de mapeamento. Esta dissertação tem por objetivo principal o estudo, implementação e avaliação de técnicas de processamento e análise de imagens visando a classificação da nuvem de pontos LiDAR (Light Detection and Ranging), e a obtenção, de forma automática, do MDT (Modelo Digital do Terreno) e dos pontos pertencentes a edificações e vegetação. Inicialmente são apresentados os conceitos necessários para o entendimento do método proposto, o qual é detalhado na sequência, assim como os conjuntos de dados utilizados para as avaliações. Além da revisão conceitual sobre tópicos como Morfologia Matemática, Análise de Componentes Principais e algoritmo RANSAC, estudou-se a necessidade de redução da quantidade de iterações do RANSAC e uma alternativa para obtenção de alguns dos parâmetros do método a priori. Foram realizados experimentos sobre a escolha do interpolador (para a geração da grade regular) e para a seleção da forma e dimensão do elemento estruturante (usado nas operações morfológicas). A classificação final foi avaliada em termos de completeza e nível de acerto, calculadas com relação a referências geradas manualmente. / The point clouds acquired by ALS (Airborne LASER Scanning) systems represent the surface with great level of detail, recording both natural vegetation and anthropic features, such as buildings and roads, for example. The automation’s task of point clouds classification is important to reduce costs in practical applications related to mapping activities and production. This work is primarily focused in the study, implementation and evaluation of image processing and analysis techniques, aiming the automatic cloud point classification, generation of the DTM (Digital Terrain Model) and the detection of roof plane and vegetation points. Besides the conceptual review about Mathematical Morphology, Principal Component Analysis and RANSAC (Random Sample Consensus), it was studied the need to reduce the quantity of iterations and an alternative to obtain some of the parameters required by RANSAC algorithm considering one preliminary classification based on Principal Component Analysis. Some experiments were conducted in order to select both the interpolation method (to generate the grid) and the shape and size of the structuring element (used in the morphological operations). The final classification was evaluated in terms of completeness and correctness, computed with respect to a manually generated reference.

Made available in DSpace on 2014-06-12T15:53:49Z (GMT). No. of bitstreams: 2 arquivo1931_1.pdf: 3171518 bytes, checksum: 18e05da39f750dea38eaa754f1aa4735 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2009 / Atualmente, com o aumento do poder computacional e os estudos em usabilidade, sistemas de tempo real e foto-realismo, os requisitos de qualquer sistema de computador são mais complexos e sofisticados. Sistemas de Realidade Aumentada não são exceção em sua tentativa de resolver problemas da vida real do usuário com um nível reduzido de risco, tempo gasto ou complexidade de aprendizado. Tais sistemas podem ser classificados como baseados em marcadores ou livres de marcadores. O papel essencial da realidade aumentada sem marcadores é evitar o uso desnecessário e indesejável de marcadores nas aplicações. Para atender à demanda por tecnologias de realidade aumentada robustas e não-intrusivas, esta dissertação propõe uma cadeia de execução para o desenvolvimento de aplicações de realidade aumentada sem marcadores, especialmente baseadas na técnica de recuperação da estrutura a partir do movimento em tempo real

The microdots are very small object. The microdots are applied in protection object. The project purpose is to find and to analyze the microdots. The project consists from two parts. A first part describes the hardware sensor construction and a second part describes the software solution. I selected the optics, camera module and illumination in the hardware part. I’m analyzing of the microdots on a picture in software part.

This thesis deals with algorithms of visual odometry and its application on the experimental vehicle Car4. The first part contains different researches in this area on which the solution process is based. Next chapters introduce theoretical design and ideas of monocular and stereo visual odometry algorithms. The third part deals with the implementation in the software MATLAB with the use of Image processing toolbox. After tests done and based on real data, the chosen algorithm is applied to the vehicle Car4 used in practical conditions of interior and exterior. The last part summarizes the results of the work and address the problems which are asociated with the application of visual obmetry algorithms.

No description available.