Robust Centroid Target Tracker Based on New Distance Features in Cluttered Image Sequences

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概要

• 論文の詳細を見る

• A real-time adaptive segmentation method based on new distance features is proposed for the binary centroid tracker. These novel features are distances between the predicted center pixel of a target object by a tracking filter and each pixel in extraction of a moving target. The proposed method restricts clutters with target-like intensity from entering a tracking window and has low computational complexity for real-time applications compared with other complex feature-based methods. Comparative experiments show that the proposed method is superior to other segmentation methods based on the intensity feature only in target detection and tracking.

• 社団法人電子情報通信学会の論文
• 2000-12-25

著者

• Park D‐j

  Korea Advanced Inst. Sci. And Technol. Daejeon Kor

• Kim D‐j

  Korea Advanced Inst. Sci. And Technol. Taejon Kor

• CHO Jae-Soo

  The Information Processing Systems Laboratory, Department of Electrical Engineering, Korea Advanced

• KIM Do-Jong

  The Information Processing Systems Laboratory, Department of Electrical Engineering, Korea Advanced

• PARK Dong-Jo

  The Information Processing Systems Laboratory, Department of Electrical Engineering, Korea Advanced

• Cho Jae-soo

  The Information Processing Systems Laboratory Department Of Electrical Engineering Korea Advanced In

関連論文

• Robust Centroid Target Tracker Based on New Distance Features in Cluttered Image Sequences
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• Overcomplete Blind Source Separation of Finite Alphabet Sources

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