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EnglishWe present a quantitative evaluation of Matrioska, a novel framework for the detection and tracking in real-time of unknown object in a video stream, on the LTDT2014 dataset that includes six sequences for the evaluation of single-object long-term visual trackers. Matrioska follows the approach of tracking by detection: the detector localizes the target object in each frame, using multiple keypoint-based methods. To account for appearance changes, the learning module updates both the target object and background model with a growing and pruning approach
| Titolo: | The matrioska tracking algorithm on LTDT2014 dataset | |
| Autori: | ||
| Data di pubblicazione: | 2014 | |
| Abstract: | We present a quantitative evaluation of Matrioska, a novel framework for the detection and tracking in real-time of unknown object in a video stream, on the LTDT2014 dataset that includes six sequences for the evaluation of single-object long-term visual trackers. Matrioska follows the approach of tracking by detection: the detector localizes the target object in each frame, using multiple keypoint-based methods. To account for appearance changes, the learning module updates both the target object and background model with a growing and pruning approach | |
| Handle: | http://hdl.handle.net/11367/44289 | |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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