{"_buckets": {"deposit": "9a481c45-a65f-4310-911d-6ac2415a541a"}, "_deposit": {"id": "21715", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "21715"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00021715", "sets": ["314"]}, "author_link": ["64481", "64482", "64483", "64484", "64485", "64486", "64487", "64488", "64489", "64490", "64491", "64492", "64493", "64494"], "item_10_alternative_title_19": {"attribute_name": "その他のタイトル", "attribute_value_mlt": [{"subitem_alternative_title": "A study on people density estimation using multiple cameras", "subitem_alternative_title_language": "en"}]}, "item_10_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2013-09", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "230", "bibliographicPageEnd": "6", "bibliographicPageStart": "1", "bibliographicVolumeNumber": "113", "bibliographic_titles": [{"bibliographic_title": "電子情報通信学会技術研究報告. PRMU, パターン認識・メディア理解", "bibliographic_titleLang": "ja"}]}]}, "item_10_description_4": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "公共の安全やマーケティングを目的として,群集の解析の研究が注目を集めている.また近年,セキュリティ意識が高まり,監視カメラから得られる大量の映像を用いて群集の行動を解析する技術が求められている.しかし,人手による解析には多くの時間や労力が必要なため,このような大量の群集映像の自動解析に関する期待は高い.群集解析の中でも,場所領域毎の人数分布の推定には一定の需要がある.そこで我々は,多数の人が密集して存在する状況下での場所領域毎の人数分布の推定を目指す.本報告では,複数カメラを用いることで遮蔽の影響に対処するとともに,回帰による小領域毎の人数推定により人数分布を推定する手法を検討する.評価実験において,提案手法の人数分布推定精度を評価した.", "subitem_description_language": "ja", "subitem_description_type": "Abstract"}, {"subitem_description": "Crowd analysis is focused on for public safety and marketing. Also, in recent years, it has become necessary to analyze a large volume of video data recording the activity of a crowd according to the widespread of surveillance cameras due to the increase of security awareness. Automatic analysis of such crowd videos is in demand because manual analysis takes time and effort. Among the crowd analysis, there is a demand for people density estimation. Therefore, we aim to estimate the density of people in a situation where many people exist, using multiple cameras to deal with occlusion. In this report, we study a method which estimates the people density by counting people based on regression in small areas. In an experiment, we examined the accuracy of the proposed people density estimation method.", "subitem_description_language": "en", "subitem_description_type": "Abstract"}]}, "item_10_description_5": {"attribute_name": "内容記述", "attribute_value_mlt": [{"subitem_description": "IEICE Technical Report;PRMU2013-56", "subitem_description_language": "en", "subitem_description_type": "Other"}]}, "item_10_identifier_60": {"attribute_name": "URI", "attribute_value_mlt": [{"subitem_identifier_type": "URI", "subitem_identifier_uri": "http://ci.nii.ac.jp/naid/110009824969/"}, {"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/2237/23864"}]}, "item_10_publisher_32": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "一般社団法人電子情報通信学会", "subitem_publisher_language": "ja"}]}, "item_10_relation_40": {"attribute_name": "シリーズ", "attribute_value_mlt": [{"subitem_relation_name": [{"subitem_relation_name_text": "IEICE Technical Report;PRMU2013-56"}]}]}, 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