ICAR was one of the organizers of the SBM-RGBD Challenge
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Luis Salgado, Tsubasa Minematsu. Lucia Maddalena
Luis Salgado, Tsubasa Minematsu. Lucia Maddalena
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Date:
11/09/2017

ICAR CNR was one of the organizers of the SBM-RGBD Challenge

(http://rgbd2017.na.icar.cnr.it/SBM-RGBDchallenge.html),  held in conjunction with the RGBD2017 Workshop (http://rgbd2017.na.icar.cnr.it/) on Background Learning for Detection and Tracking from RGBD Videos.

The aim of the challenge was to evaluate and compare scene background modeling methods for the detection of moving objects on the RGBD videos of the SBM-RGBD dataset (http://rgbd2017.na.icar.cnr.it/SBM-RGBDdataset.html).

Researchers from academia and industry were invited to test their moving object detection algorithms on the SBM-RGBD dataset and report the results to participate in the challenge. The submitted results are reported on the challenge webpage.

The winners were Tsubasa Minematsu, Atsushi Shimada, Hideaki Uchiyama, e Rin-ichiro Taniguchi, authors of the SCAD algorithm, described in the paper “Simple Combination of Appearance and Depth for Foreground Segmentation”, in S. Battiato, G. Gallo, G.M. Farinella, M. Leo (Eds), New Trends in Image Analysis and Processing-ICIAP 2017 Workshops, Lecture Notes in Computer Science, Springer, 2017 (https://link.springer.com/chapter/10.1007/978-3-319-70742-6_25).

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