We address the problem of identifying objects of interest in 3D images as a set of related tasks involving localization of objects within a scene, segmentation of observed object instances from other scene elements, classifying detected objects into semantic categories, and estimating the 3D pose of detected objects within the scene. The increasing availability of 3D sensors motivates us to leverage large amounts of 3D data to train machine learning models to address these tasks in 3D images. Leveraging recent advances in deep learning has allowed us to develop models capable of addressing these tasks and optimizing these tasks jointly to reduce potential errors propagated when solving these tasks independently.
","abstract_html":"<p>We address the problem of identifying objects of interest in 3D images as a set of related tasks involving localization of objects within a scene, segmentation of observed object instances from other scene elements, classifying detected objects into semantic categories, and estimating the 3D pose of detected objects within the scene. The increasing availability of 3D sensors motivates us to leverage large amounts of 3D data to train machine learning models to address these tasks in 3D images. Leveraging recent advances in deep learning has allowed us to develop models capable of addressing these tasks and optimizing these tasks jointly to reduce potential errors propagated when solving these tasks independently.</p>","abstract_has_math":false,"creators":["Zelener, Allan"],"institution":"The Graduate School and University Center of The City University of New York","degree_name":"Doctor of Philosophy","degree_level":"Doctoral","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":[],"advisors":["Ioannis Stamos"],"committee_chairs":[],"committee_members":["Yingli Tian","Andrew Rosenberg","Philippos Mordohai"],"year":2018,"date_issued":"2018-02-01T08:00:00Z","date_published":"2018-02-01T08:00:00Z","updated_at":"2026-07-24T02:00:35Z","subjects":["Artificial Intelligence and Robotics","Computer Sciences","machine learning","neural networks","deep learning","computer vision","lidar"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://academicworks.cuny.edu/gc_etds/2531","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Ioannis Stamos"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Yingli Tian","Andrew Rosenberg","Philippos Mordohai"]},{"key":"dc:creator","label":"Author","values":["Zelener, Allan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2018-01-28T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The Graduate School and University Center of The City University of New York"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Artificial Intelligence and Robotics","Computer Sciences","machine learning","neural networks","deep learning","computer vision","lidar"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://academicworks.cuny.edu/gc_etds/2531"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["We address the problem of identifying objects of interest in 3D images as a set of related tasks involving localization of objects within a scene, segmentation of observed object instances from other scene elements, classifying detected objects into semantic categories, and estimating the 3D pose of detected objects within the scene. The increasing availability of 3D sensors motivates us to leverage large amounts of 3D data to train machine learning models to address these tasks in 3D images. Leveraging recent advances in deep learning has allowed us to develop models capable of addressing these tasks and optimizing these tasks jointly to reduce potential errors propagated when solving these tasks independently.
"]},{"key":"dc:title","label":"Title","values":["Object Localization, Segmentation, and Classification in 3D Images"]}]}],"canonical_facts":{"dc:contributor.advisor":["Ioannis Stamos"],"dc:contributor.committeemember":["Yingli Tian","Andrew Rosenberg","Philippos Mordohai"],"dc:creator":["Zelener, Allan"],"dc:date.available":["2018-01-28T08:00:00Z"],"dc:description.abstract":["We address the problem of identifying objects of interest in 3D images as a set of related tasks involving localization of objects within a scene, segmentation of observed object instances from other scene elements, classifying detected objects into semantic categories, and estimating the 3D pose of detected objects within the scene. The increasing availability of 3D sensors motivates us to leverage large amounts of 3D data to train machine learning models to address these tasks in 3D images. Leveraging recent advances in deep learning has allowed us to develop models capable of addressing these tasks and optimizing these tasks jointly to reduce potential errors propagated when solving these tasks independently.
"],"dc:identifier":["https://academicworks.cuny.edu/gc_etds/2531"],"dc:subject":["Artificial Intelligence and Robotics","Computer Sciences","machine learning","neural networks","deep learning","computer vision","lidar"],"dc:title":["Object Localization, Segmentation, and Classification in 3D Images"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Doctoral"],"thesis:degree_name":["Doctor of Philosophy"],"thesis:institution_name":["The Graduate School and University Center of The City University of New York"]},"updated_at":"2026-07-24T02:00:35Z"}