2026-09-19T16:02:15Zhttps://dspace.mit.edu/server/oai/request

oai:dspace.mit.edu:1721.1/1131172026-06-06T00:55:28Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023

Kamal Youcef-Toumi. Paerhati, Paruku Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2018-01-12T20:57:07Z 2018-01-12T20:57:07Z 2017 2017 http://hdl.handle.net/1721.1/113117 1016453717 Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (page 48). Vision is one of the most powerful senses available to creatures. Undoubtedly, many of the fundamental operations of humans, such as the ability to plan paths, avoid obstacles, and recognize objects, depend heavily on their visual perception of the world around them. Although humans have naturally evolved to efficiently use their stereo optical prowess to develop an understanding of their environment, artificial machines and systems in comparison have just begun to utilize computer vision to create awareness of local physical entities. One of the most important sensory skills creatures have is depth perception, which allows them to estimate the relative distance of objects in their vision from many visual cues. Many systems have been developed to aid machines in perceiving the depth map of their environment, and each system has its drawbacks and benefits. In this paper, we introduce the design and implementation of a new system which provides a depth map from the use of a single optical camera with focal plane variation in the images taken. The paper focuses on the methods used to scale the depth from focus algorithm to perform in real-time. The results also showcase a real-time depth mapping system capable of providing rich depth maps of scenes at a high framerate and with advanced noise filtration techniques. by Paruku Paerhati. M.Eng. 49 pages eng Massachusetts Institute of Technology MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 Electrical Engineering and Computer Science. Real-time monocular depth mapping system using variance of focal plane and pixel focus measure Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="ab75a7f2-1506-4024-9a09-1d19512532fa"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Real-time monocular depth mapping system using variance of focal plane and pixel focus measure</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2017</PublicationDate> <Authors> <Author> <DisplayName>Paerhati, Paruku</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>Vision is one of the most powerful senses available to creatures. Undoubtedly, many of the fundamental operations of humans, such as the ability to plan paths, avoid obstacles, and recognize objects, depend heavily on their visual perception of the world around them. Although humans have naturally evolved to efficiently use their stereo optical prowess to develop an understanding of their environment, artificial machines and systems in comparison have just begun to utilize computer vision to create awareness of local physical entities. One of the most important sensory skills creatures have is depth perception, which allows them to estimate the relative distance of objects in their vision from many visual cues. Many systems have been developed to aid machines in perceiving the depth map of their environment, and each system has its drawbacks and benefits. In this paper, we introduce the design and implementation of a new system which provides a depth map from the use of a single optical camera with focal plane variation in the images taken. The paper focuses on the methods used to scale the depth from focus algorithm to perform in real-time. The results also showcase a real-time depth mapping system capable of providing rich depth maps of scenes at a high framerate and with advanced noise filtration techniques.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>