21 research outputs found

    IMAGE DISTORTION CORRECTION FOR BIPRISM-BASED SINGLE-LENS STEREOVISION SYSTEM

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    Ph.DDOCTOR OF PHILOSOPH

    Computer Vision Applications in the Navigation of Unmanned Underwater Vehicles

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    Single View Modeling and View Synthesis

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    This thesis develops new algorithms to produce 3D content from a single camera. Today, amateurs can use hand-held camcorders to capture and display the 3D world in 2D, using mature technologies. However, there is always a strong desire to record and re-explore the 3D world in 3D. To achieve this goal, current approaches usually make use of a camera array, which suffers from tedious setup and calibration processes, as well as lack of portability, limiting its application to lab experiments. In this thesis, I try to produce the 3D contents using a single camera, making it as simple as shooting pictures. It requires a new front end capturing device rather than a regular camcorder, as well as more sophisticated algorithms. First, in order to capture the highly detailed object surfaces, I designed and developed a depth camera based on a novel technique called light fall-off stereo (LFS). The LFS depth camera outputs color+depth image sequences and achieves 30 fps, which is necessary for capturing dynamic scenes. Based on the output color+depth images, I developed a new approach that builds 3D models of dynamic and deformable objects. While the camera can only capture part of a whole object at any instance, partial surfaces are assembled together to form a complete 3D model by a novel warping algorithm. Inspired by the success of single view 3D modeling, I extended my exploration into 2D-3D video conversion that does not utilize a depth camera. I developed a semi-automatic system that converts monocular videos into stereoscopic videos, via view synthesis. It combines motion analysis with user interaction, aiming to transfer as much depth inferring work from the user to the computer. I developed two new methods that analyze the optical flow in order to provide additional qualitative depth constraints. The automatically extracted depth information is presented in the user interface to assist with user labeling work. In this thesis, I developed new algorithms to produce 3D contents from a single camera. Depending on the input data, my algorithm can build high fidelity 3D models for dynamic and deformable objects if depth maps are provided. Otherwise, it can turn the video clips into stereoscopic video

    Pedestrian detection and tracking using stereo vision techniques

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    Automated pedestrian detection, counting and tracking has received significant attention from the computer vision community of late. Many of the person detection techniques described so far in the literature work well in controlled environments, such as laboratory settings with a small number of people. This allows various assumptions to be made that simplify this complex problem. The performance of these techniques, however, tends to deteriorate when presented with unconstrained environments where pedestrian appearances, numbers, orientations, movements, occlusions and lighting conditions violate these convenient assumptions. Recently, 3D stereo information has been proposed as a technique to overcome some of these issues and to guide pedestrian detection. This thesis presents such an approach, whereby after obtaining robust 3D information via a novel disparity estimation technique, pedestrian detection is performed via a 3D point clustering process within a region-growing framework. This clustering process avoids using hard thresholds by using bio-metrically inspired constraints and a number of plan view statistics. This pedestrian detection technique requires no external training and is able to robustly handle challenging real-world unconstrained environments from various camera positions and orientations. In addition, this thesis presents a continuous detect-and-track approach, with additional kinematic constraints and explicit occlusion analysis, to obtain robust temporal tracking of pedestrians over time. These approaches are experimentally validated using challenging datasets consisting of both synthetic data and real-world sequences gathered from a number of environments. In each case, the techniques are evaluated using both 2D and 3D groundtruth methodologies

    Real Time Log Length Measurement Using GPU Accelerated Visual Odometry

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    This thesis studies GPU accelerated visual odometry in measuring log length. The visual odometry would not suffer slippage nor require recalibration depending type of wood or temperature conditions compared to mechanical measurement. The requirement of the real-time performance is quite high. Image capturing in 120 Hz frequency is needed as log is moved several meters per second by harvester heads. Here GPU acceleration will be used as it can give speedup in magnitude of hundreds or more. Real-time performance is targeted by selecting fast algorithms for subtasks of measurement pipeline and considering possibilities to parallelize algorithm. In many cases performance boost is achieved, but not in expected magnitude. Physical constraints of the graphics card hardware become easily the limiting factor in parallelization. Real-time performance was achieved in this thesis but not with required accuracy. It remained for future work to find out which algorithms would give both targets.  Taman lisensiaatintutkimuksen aiheena on GPU laskennan kaytto konenäköön perustuvassa tukin pituuden mittauksessa. Konenäköön perustuva pituuden mittaus ei tarvitse uudelleen kalibrointia puulajin tai lämpötilan mukaan. Konenäköön perustuvassa mittauksessa myöskaan mittapyöra ei voi luistaa tukin pinnalla. Realiaikaisuuden vaatimus on tässä sovelluksessa korkea. Kuvat on otettu 120 Hz taajuudella, koska leikkuupää liikuttaa tukkia useita metrejä sekunnissa. GPU laskenta potentiaalisesti nopeuttaisi laskentaa tarvittavissa määrin. Realiaikaista vastetta haettiin seka algoritmien valinnalla etta harkitsemalla mahdollisuuksia rinnaisohjelmoinnin käyttämiseen. Monessa tapauksessa vasteet paranivat, vaikka grafiikkakortin ominaisuudet usein rajoittivat rinnaikkaisohjelmoinnista saatavaa hyötyä. Realiaikainen vaste saavutettiin, mutta ei tarvittavalla pituuden mittaamisen tarkkuudella. Molempien tavoitteiden saavuttaminen jai mahdollisten jatkotöiden tehtäväksi
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