The Matrioska Tracking Algorithm on LTDT2014 Dataset

Mario Edoardo Maresca, Alfredo Petrosino; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2014, pp. 706-711

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.

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[bibtex]
@InProceedings{Maresca_2014_CVPR_Workshops,
author = {Edoardo Maresca, Mario and Petrosino, Alfredo},
title = {The Matrioska Tracking Algorithm on LTDT2014 Dataset},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2014}
}