著者

井元 大輔 黒沢 健至 土屋 兼一 黒木 健郎 平林 学人 秋葉 教充 角田 英俊

出版者

日本法科学技術学会

雑誌

日本法科学技術学会誌 (ISSN:18801323)

巻号頁・発行日

vol.24, no.1, pp.23-41, 2019 (Released:2019-01-31)

参考文献数

17

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Gait recognition is one of recently evolving techniques by which we can recognize individuals by one's gait. There are two major approaches; silhouette-based and model-based. In Japan, a method based on GEI (Gait Energy Image), which is one of the silhouette-based approaches, is used for forensic purposes. Sometimes, it is a problem of silhouettes' variabilities in one person due to different clothing that lessen recognition reliability under the GEI method. Here, we analyzed and evaluated the average error rates under clothing variation conditions using the method called Dynamic-features method, which we previously proposed. The Dynamic-features method was built inspired by previous studies of model-based gait recognition, which uses time-series of feature points and local shape features around the points automatically extracted from silhouette sequences. Before analysis, we roughly categorize whole data in the OU-ISIR gait database -treadmill dataset B-, which contains side-view data, into five clothing categories in order to deal with realistic off-line forensic situation, where we cannot strictly control the clothing conditions. As a result, the average increases of average error rate of GEI-based methods due to different clothing were ranged from approximately 8 to 11%, whereas that of the Dynamic-features method was approximately 3%. It was found that two representative dynamics of a feature point of one same person, where the point is influenced by different clothing conditions, showed different mean values but showed similar trends. Based on this fact, it is suggested that robustness of performances in Dynamic-features method under clothing variation conditions is obtained by effective utilization of dynamic properties of human's gait.

著者

黒沢健至 黒木健郎 土屋兼一

雑誌

研究報告コンピュータビジョンとイメージメディア(CVIM)

巻号頁・発行日

vol.2013, no.25, pp.1-1, 2013-03-07

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街頭防犯カメラや携帯カメラ等の増加に伴い,犯罪捜査などの警察活動における画像(映像)分析の重要性が増している.近年では,画像分析は基本的な捜査手法の一つと位置付けられているが,現場捜査員からの期待も大きく,新しい解析技術の開発も求められ業務が拡大している分野である.本報では,科学警察研究所の物理研究室でこれまでに扱った各種画像解析について,実例を交えながら概説する.特に,撮像素子の固定パターン雑音(FPN)の固有性を利用した撮影カメラの個体識別法について,その識別原理や効果的事例,さらに画像改ざんの検出へ応用できることを示す.また,マルチフレーム超解像などの画質改善処理や,幾何解析等についても我々の取り組みを紹介する.最後に,画像分析に関する警察活動の現場での問題点や,CVIM研究会等の画像工学研究者への期待を述べる.