Multivariate probability distribution based sports highlight detection

Abstract

A method detects sports highlights for an event involving players and a play object. The method calculates a covariance matrix characterizing a two-dimensional variation of a multivariate probability distribution presumed for the players relative to a spatiotemporal tracking dataset corresponding to the players. The method calculates an area S occupied by the distribution as a function S(t) based on Eigenvalues calculated from the covariance matrix, derives a differential of the function S(t) and obtains an absolute value of the differential using a function ƒ(t). The method defines a function g(t) relative to a threshold t. The function g(t) assigns a first or second value responsive to a current time t meeting or exceeding, respectively, the threshold t. The method outputs as the sports highlight, a highest value from among local peaks extracted from a convolution of the functions ƒ(t) and g(t) and being within a range of the threshold t.