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The Matrioska Tracking Algorithm on LTDT2014 Dataset

Mario Edoardo Maresca, Alfredo Petrosino
CVPRW 2014 pp. 720-725
doi:10.1109/CVPRW.2014.128 /cvprw/2014/maresca2014cvprw-matrioska/

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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Cite

Text

Maresca and Petrosino. "The Matrioska Tracking Algorithm on LTDT2014 Dataset." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2014. doi:10.1109/CVPRW.2014.128

Markdown

[Maresca and Petrosino. "The Matrioska Tracking Algorithm on LTDT2014 Dataset." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2014.](https://mlanthology.org/cvprw/2014/maresca2014cvprw-matrioska/) doi:10.1109/CVPRW.2014.128

BibTeX

@inproceedings{maresca2014cvprw-matrioska,
  title     = {{The Matrioska Tracking Algorithm on LTDT2014 Dataset}},
  author    = {Maresca, Mario Edoardo and Petrosino, Alfredo},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2014},
  pages     = {720-725},
  doi       = {10.1109/CVPRW.2014.128},
  url       = {https://mlanthology.org/cvprw/2014/maresca2014cvprw-matrioska/}
}