{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/ego2top-matching-viewers-in-egocentric-and","title":"Ego2Top: Matching Viewers in Egocentric and Top-view Videos","arxiv_id":"1607.06986","date":"2016-07-24","proceeding":null,"authors":["Shervin Ardeshir","Ali Borji"],"abstract":"Egocentric cameras are becoming increasingly popular and provide us with\nlarge amounts of videos, captured from the first person perspective. At the\nsame time, surveillance cameras and drones offer an abundance of visual\ninformation, often captured from top-view. Although these two sources of\ninformation have been separately studied in the past, they have not been\ncollectively studied and related. Having a set of egocentric cameras and a\ntop-view camera capturing the same area, we propose a framework to identify the\negocentric viewers in the top-view video. We utilize two types of features for\nour assignment procedure. Unary features encode what a viewer (seen from\ntop-view or recording an egocentric video) visually experiences over time.\nPairwise features encode the relationship between the visual content of a pair\nof viewers. Modeling each view (egocentric or top) by a graph, the assignment\nprocess is formulated as spectral graph matching. Evaluating our method over a\ndataset of 50 top-view and 188 egocentric videos taken in different scenarios\ndemonstrates the efficiency of the proposed approach in assigning egocentric\nviewers to identities present in top-view camera. We also study the effect of\ndifferent parameters such as the number of egocentric viewers and visual\nfeatures.","url_abs":"http://arxiv.org/abs/1607.06986v2","url_pdf":"http://arxiv.org/pdf/1607.06986v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"graph-matching","task_name":"Graph Matching"}],"methods":[],"datasets_introduced":[{"slug":"ego2top","name":"Ego2Top","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1607.06986","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}