Proceedings of ACM Multimedia 2015
A. Ortis, G. M. Farinella, S. Battiato
Image Processing Laboratory -
University of Catania
{ortis, gfarinella, battiato}@unict.it
V. D'Amico, L. Addesso, G. Torrisi
JOL WAVE - Telecom Italia
{valeria1.damico, luca.addesso, giovanni.torrisi}@telecomitalia.it
To evaluate the performances of the proposed method on each scenario we compute two measures obtained from the following scores computed on each clustering over time:
From the above scores, we compute the weighted mean of the ratios Pa/Pr and
Pg/Pr over all the segmented blocks of a video, where the weights are given
by the length of the blocks (i.e., the number of frames). When Pa/Pr is
close to 1 the popularity score computed by our method is similar to the
ground truth popularity. When this number is greater than 1 it means that
the most popular cluster obtained with our approach is affected by outliers,
whereas when this number is less than 1 it means that the our method missed
some element of the ground truth popular cluster. Since Pa/Pr deal just with
the number of video in the popular cluster, it is useful to look also at the
ratio Pg/Pr. Indeed, Pg/Pr assesses the visual content of the videos in the
popular cluster (true positive). This score have to be close to 1 to
indicate accuracy in the popular cluster computed by our method.
The obtained results with respect to the different scenarios are reported in the
Table below.
Scenario | Devices | Models | Pa/Pr | Pg/Pr |
---|---|---|---|---|
Foosball | 4 | 2 | 1.02 | 1 |
Meeting | 2 | 2 | 1.01 | 0.99 |
Meeting | 4 | 4 | 0.99 | 0.95 |
Meeting | 5 | 5 | 0.89 | 0.76 |
SAgata | 7 | 6 | 1.05 | 1 |
Concert [1] | 3 | 1 | 1.06 | 1 |
Lecture [1] | 3 | 1 | 1.05 | 0.86 |
Seminar [1] | 3 | 1 | 0.62 | 0.62 |
[1] Y. Hoshen, G. Ben-Artzi, and S. Peleg. Wisdom of the crowd in egocentric video curation. In IEEE Conference on Computer Vision and Pattern Recognition Workshops, pages 587-593.