High-Tech Video Capture and Analysis for Counting Park Users
Today’s technology could contribute substantially to measuring physical activity. The current study evaluated traditional and novel approaches for assessing park use. The traditional approach involved a trained observer performing the System for Observing Play and Recreation in Communities (SOPARC) at 14 parks while wearing a point-of-view, wearable video device (WVD). The novel approach utilized computer vision to count park users in the WVD videos taken during in-person SOPARCs. Both approaches were compared to criterion counts from expert reviews of the WVD videos. In the 676 scans made during in-person SOPARCs, 293 individuals were observed while 341 were counted by experts in the corresponding WVD videos. When using scans/videos having individuals in them (84 scans/videos), intra-class correlations (ICC) indicated good-to-excellent reliability between in-person SOPARC and experts for counts of total women and men, within age groups (except seniors), of Blacks and Whites, and within intensity categories (ICCs > .87; p < 0.001). In a subsample of 42 scans/videos, 174 individuals were counted using computer vision and 213 by experts. When using 27 of the 42 WVD videos with individuals in them, ICCs indicated good reliability between computer vision and expert reviews (ICC = .83; p < 0.001). Bland-Altman analysis showed the concurrence of expert counts with both in-person SOPARC and computer vision counts decreased as the number of individuals in a scan/video increased. The results of this study support the use of a highly discrete method for obtaining point-of-view videos and the application of computer vision for automating the counting of park users in the videos.