著者

我妻 路人 辻 亮 秋田 真志 Michito AGATSUMA Akira TSUJI Masashi AKITA

出版者

甲南大学法学会

雑誌

甲南法学 = Konan Hogaku : Konan Law Review (ISSN:04524179)

巻号頁・発行日

vol.60, no.1, pp.243-267, 2020-03-31

著者

榎原 博之 中山 弘基 飯田 修平 長辻 亮太

雑誌

情報処理学会論文誌 (ISSN:18827764)

巻号頁・発行日

vol.57, no.1, pp.331-342, 2016-01-15

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近年,メタヒューリスティクスは組合せ最適化問題を解く手法として多くの研究が行われている.最近の研究では,コンサルタント誘導型探索(CGS)と呼ばれる新しいメタヒューリスティクスが提案されている.本研究では,CGSを用いた巡回セールスマン問題(TSP)に対する並列アルゴリズムを提案する.アルゴリズムの並列化では,CGSにおける仮想人間をそれぞれの計算機の各プロ セッサコアに割り当てることで効率良く解の探索を行う.また,仮想人間の集団を複数のサブ集団に分割し,各サブ集団どうしで仮想人間の移住を行う島モデルをCGSに取り入れる.10台の計算機を用いた性能評価実験を行い,都市数が5,000のTSPLIBのベンチマーク問題例に対して5%未満の誤差率を達成することを示す.

著者

今井 順一 柏木 雄平 木辻 亮

出版者

公益社団法人 計測自動制御学会

雑誌

計測自動制御学会論文集 (ISSN:04534654)

巻号頁・発行日

vol.55, no.5, pp.342-352, 2019

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<p>Visual object tracking techniques are widely required by many vision applications. The color-based particle filter is known as one of useful methods for robust object tracking. However, the conventional color-based particle filter has a problem that it is not robust against self-occlusion. Self-occlusion occurs when a part of a target object is hidden by itself from a camera. When the target object moves or rotates, a part of the target disappears because the self-occlusion occurs and other part appears because the self-occlusion is resolved. The conventional color-based particle filter often fails to follow such a change of the target's appearance due to self-occlusion during the tracking process. In this paper, we propose a novel method for robust object tracking against the self-occlusion. The proposed method is based on the color-based particle filter, and it also uses depth information obtained by an RGB-D camera. When the self-occlusion occurs and the target's appearance changes, the proposed method extracts a region for the target object in the input image by the graph cuts based on depth information. However, this process often includes unnecessary regions, especially when some objects are close to the target. Then, the proposed method distinguishes the region for the target from unnecessary ones by investigating expanse of colors around the target. Therefore, the target model is correctly updated and the robust tracking is achieved. In order to verify the effectiveness of the proposed method, we carried out an experiment to compare the proposed method with the conventional one. Experimental results show that the proposed method works well.</p>