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 id : |
1110
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| type : |
MSc_Thesis
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| dateandtime : |
2024-04-22 13:00:00
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| duration : |
90 min.
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Recommended duration for PhD thesis is 90 minutes, for other seminar types, it is 60 minutes. The duration specified here is used to reserve the room.
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| place : |
A105
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| departmental : |
yes
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| title : |
REAL-TIME JOINT MULTI-CAMERA MULTI-PERSON TRACKING
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| author : |
ABDUSSAMET TARIK TEMUR
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| supervisors : |
ASSOC.PROF.DR.EMRE AKBAS
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Supervisors field is applicable especially for a Thesis Defense
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| company : |
Computer Engineering Dept. Middle East Technical Univ.
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| country : |
Turkey
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| abstract : |
This study aims to construct a Real-Time Multi-Camera Multi-Person Tracking (MC-MOT) system which jointly optimizes local (single-camera) and global (multi-camera) feature distances. While most existing approaches follow a two-stage track-then-associate scheme, this work focuses on a joint approach. Our method also operates in real-time in contrast to the more common offline or windowed joint tracking algorithms which operate on future information. In summary, this study contributes: (i) A joint MCMOT formulation where the optimization objective solves both local and global tracking at teach step, (ii) a realization of the method in the form of an algorithm capable of producing real-time track IDs, and (iii) a new MCMOT evaluation metric we call Global IDF1 which acts as a multi-camera extension of the IDF1 metric, emphasizing continuous traceability of a target across a multi-camera network. We further propose a Multi-View Fusion (MVF) network to extract descriptive feature vectors for multi-camera detection groups. We report results comparable to offline state-of-the-art methods while remaining real-time and retaining simplicity.
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final
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