Fig. 2.

Steps to extract the dominant CAP-set for each cluster number k. (1) extract k CAPs, and their temporal occurrence fractions, ‘TF’; (2) reorder the k CAPs in descending TF as CAP¹, CAP², ... CAP^k; (3) compute ${\left\{r_m^s\right\}}_{1\le m\le k}$ , spatial similarity of the weighted (by TF) average of the top-ranked CAPs with the overall frame average. Top-ranked CAPs {CAP^j}1≤j≤n with $\{r_{n-1}^s<r_{thres}^s\}$ & $\left\{{\prod }_{p\ge n}\mathit{I}\{r_p^s\ge r_{thres}^s\}\right\}$ (in red rectangle) comprise the dominant CAP-set at k.