{"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/analyzing-first-person-stories-based-on","title":"Analyzing First-Person Stories Based on Socializing, Eating and Sedentary Patterns","arxiv_id":"1707.07863","date":"2017-07-25","proceeding":null,"authors":["Pedro Herruzo","Laura Portell","Alberto Soto","Beatriz Remeseiro"],"abstract":"First-person stories can be analyzed by means of egocentric pictures acquired\nthroughout the whole active day with wearable cameras. This manuscript presents\nan egocentric dataset with more than 45,000 pictures from four people in\ndifferent environments such as working or studying. All the images were\nmanually labeled to identify three patterns of interest regarding people's\nlifestyle: socializing, eating and sedentary. Additionally, two different\napproaches are proposed to classify egocentric images into one of the 12 target\ncategories defined to characterize these three patterns. The approaches are\nbased on machine learning and deep learning techniques, including traditional\nclassifiers and state-of-art convolutional neural networks. The experimental\nresults obtained when applying these methods to the egocentric dataset\ndemonstrated their adequacy for the problem at hand.","url_abs":"http://arxiv.org/abs/1707.07863v1","url_pdf":"http://arxiv.org/pdf/1707.07863v1.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":[{"paper_slug":"analyzing-first-person-stories-based-on","repo_url":"https://github.com/alsoba13/LAP-Annotation-Tool","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}