| Literature DB >> 30475901 |
Marcos Cruz, Javier González-Villa.
Abstract
[This corrects the article DOI: 10.1371/journal.pone.0206091.].Year: 2018 PMID: 30475901 PMCID: PMC6258239 DOI: 10.1371/journal.pone.0208359
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 3Crowd counting dataset.
15 manually annotated point patterns selected at random from the crowd counting dataset. The total number of point patterns in the dataset is 51.
Fig 4Empirical squared coefficient of error for fixed parameter values.
(A, B, C): Empirical squared coefficient of error of the 51 point patterns in the crowd counting dataset, for fixed sampling fractions f = 0.02, 0.04, 0.06 respectively. Population and sample sizes are shown on the x axis. Blue and red color represent initial number of quadrats n0 = 50, 100 respectively. Broken horizontal lines correspond to 5%, 10% and 15%, whereas the vertical broken is drawn at sample size Q = 50. (D, E, F): Analogous plots for nonempty quadrats n. Broken horizontal lines correspond to 20, 30 and 50 quadrats.
Fig 5Empirical coefficient of error for optimal parameter values.
(A): Empirical coefficient of error, obtained with sampling fractions adapted to each of the 51 point patterns considered in Fig 4. Blue, red and green colors represent sample sizes Q = 50, Q = 100 and Q = 200 respectively. Initial number of quadrats was set to n0 = 100 for all cases. (B): Analogous plots for nonempty quadrats n. The broken horizontal lines are as in Fig 4.