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Gotowe bibliografie tematyczne / Structure- Motion

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Gotowa bibliografia na temat „Structure- Motion”

Autor: Grafiati

Data publikacji: 6 września 2023

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Rozprawy doktorskie na temat "Structure- Motion"

1

Scheffler, Carl. "Articulated structure from motion." Thesis, University of the Western Cape, 2004. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=init_2988_1177923873.

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The structure from motion (SfM) problem is that of determining 3-dimensional (3D) information of a scene from sequences of 2-dimensional (2D) images [59]. This information consists of object shape and motion and relative camera motion. In general, objects may undergo complex non-rigid motion and may be occluded by other objects or themselves. These aspects make the general SfM problem under-constrained and the solution subject to missing or incomplete data.

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Svensson, Fredrik. "Structure from Forward Motion." Thesis, Linköpings universitet, Bildbehandling, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-60136.

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This master thesis investigates the difficulties of constructing a depth map using one low resolution grayscale camera mounted in the front of a car. The goal is to produce a depth map in real-time to assist other algorithms in the safety system of a car. This has been shown to be difficult using the evaluated combination of camera position and choice of algorithms. The main problem is to estimate an accurate optical flow. Another problem is to handle moving objects. The conclusion is that the implementations, mainly triangulation of corresponding points tracked using a Lucas Kanade tracker, p

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Wong, Kwan-Yee Kenneth. "Structure and motion from silhouettes." Thesis, University of Cambridge, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.621379.

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4

Zucchelli, Marco. "Optical Flow Based Structure from Motion." Doctoral thesis, KTH, Numerical Analysis and Computer Science, NADA, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3377.

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5

Orthey, Andreas. "Exploiting structure in humanoid motion planning." Phd thesis, Toulouse, INPT, 2015. http://oatao.univ-toulouse.fr/14685/1/orthey.pdf.

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If humanoid robots should work along with humans and should be able to solve repetitive tasks, we need to enable them with a skill to autonomously plan motions. Motion planning is a longstanding core problem in robotics, and while its algorithmic foundation has been studied in depth, motion planning is still an NP-hard problem lacking efficient solutions. We want to open up a new perspective on the problem by highlighting its structure: the behavior of the robot, the mechanical system of the robot, and the environment of the robot. We will investigate the hypothesis that each structural compon

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Hedborg, Johan. "Motion and Structure Estimation From Video." Doctoral thesis, Linköpings universitet, Datorseende, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-76904.

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Digital camera equipped cell phones were introduced in Japan in 2001, they quickly became popular and by 2003 outsold the entire stand-alone digital camera market. In 2010 sales passed one billion units and the market is still growing. Another trend is the rising popularity of smartphones which has led to a rapid development of the processing power on a phone, and many units sold today bear close resemblance to a personal computer. The combination of a powerful processor and a camera which is easily carried in your pocket, opens up a large eld of interesting computer vision applications. The c

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7

Örjehag, Erik. "Unsupervised Learning for Structure from Motion." Thesis, Linköpings universitet, Datorseende, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-173731.

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Perception of depth, ego-motion and robust keypoints is critical for SLAM andstructure from motion applications. Neural networks have achieved great perfor-mance in perception tasks in recent years. But collecting labeled data for super-vised training is labor intensive and costly. This thesis explores recent methodsin unsupervised training of neural networks that can predict depth, ego-motion,keypoints and do geometric consensus maximization. The benefit of unsuper-vised training is that the networks can learn from raw data collected from thecamera sensor, instead of labeled data. The thesis

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8

Hakl, Henri. "Structure-from-motion for enclosed environments." Thesis, Link to the online version, 2007. http://hdl.handle.net/10019.1/1195.

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Rautenbach, Pieter Albertus. "Facial Feature Reconstruction using Structure from Motion." Thesis, Link to the online version, 2005. http://hdl.handle.net/10019/1340.

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10

Ji, Hui. "A holistic approach to structure from motion." College Park, Md. : University of Maryland, 2006. http://hdl.handle.net/1903/3807.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2006.<br>Thesis research directed by: Computer Science. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

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