{"id":{"repo_id":"byu","oai_identifier":"oai:scholarsarchive.byu.edu:etd-2041"},"canonical_url":"https://search.dev.ndltd.org/etd/byu/oai:scholarsarchive.byu.edu:etd-2041","repository":{"repo_id":"byu","name":"Brigham Young University","base_url":"https://scholarsarchive.byu.edu/do/oai/"},"display":{"title":"Obstacle Annotation by Demonstration","abstract":"By observing human driving with a “digital head\" (combined video camera and accelerometers) and taking a few hand annotations, we can automatically annotate regions in a robot's field of view that should be interpreted as obstacles to be avoided. This is accomplished by detecting the movement for a given frame in a video. Some hand annotations of video frames are necessary and they are used to create Probability Grids. Using the movement data and the Probability Grids, it is possible to annotate large amounts of video data quickly in an automated system.","abstract_html":"By observing human driving with a “digital head" (combined video camera and accelerometers) and taking a few hand annotations, we can automatically annotate regions in a robot's field of view that should be interpreted as obstacles to be avoided. This is accomplished by detecting the movement for a given frame in a video. Some hand annotations of video frames are necessary and they are used to create Probability Grids. Using the movement data and the Probability Grids, it is possible to annotate large amounts of video data quickly in an automated system.","abstract_has_math":false,"creators":["Clement, Michael David"],"institution":"Brigham Young University - Provo","degree_name":"MS","degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T01:28:46Z","subjects":["digital head","video","annotation","robot","obstacle","Computer Sciences"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarsarchive.byu.edu/etd/1042","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Clement, Michael David"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2007-03-08T08:00:00Z"]},{"key":"dc:publisher","label":"Institution","values":["Brigham Young University - Provo"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["digital head","video","annotation","robot","obstacle","Computer Sciences"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarsarchive.byu.edu/etd/1042","https://scholarsarchive.byu.edu/context/etd/article/2041/viewcontent/ETD_CISOPTR_934.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Physical and Mathematical Sciences; Computer Science"]},{"key":"dc:description.abstract","label":"Abstract","values":["By observing human driving with a “digital head\" (combined video camera and accelerometers) and taking a few hand annotations, we can automatically annotate regions in a robot's field of view that should be interpreted as obstacles to be avoided. This is accomplished by detecting the movement for a given frame in a video. Some hand annotations of video frames are necessary and they are used to create Probability Grids. Using the movement data and the Probability Grids, it is possible to annotate large amounts of video data quickly in an automated system."]},{"key":"dc:format","label":"Dc Format","values":["application:pdf"]},{"key":"dc:source","label":"Dc Source","values":["Brigham Young University - Provo"]},{"key":"dc:title","label":"Title","values":["Obstacle Annotation by Demonstration"]}]}],"canonical_facts":{"dc:creator":["Clement, Michael David"],"dc:date":["2007-03-08T08:00:00Z"],"dc:description":["Physical and Mathematical Sciences; Computer Science"],"dc:description.abstract":["By observing human driving with a “digital head\" (combined video camera and accelerometers) and taking a few hand annotations, we can automatically annotate regions in a robot's field of view that should be interpreted as obstacles to be avoided. This is accomplished by detecting the movement for a given frame in a video. 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