Play Estimation with Motions and Textures in Space-Time Map Description

Abstract

It is easy to retrieve the small size parts from small videos. It is also easy to retrieve the middle size part from large videos. However, we have difficulties to retrieve the small size parts from large videos. We have large needs for estimating plays in sport videos. Plays in sports are described as the motions of players. This paper proposes the play retrieving method based on both of the motion compensation vector and normal color frames in MPEG sports videos. In MPEG videos, there are motion compensation vectors. Using the motion compensation vectors, we do not need to estimate the motion vectors between adjacent frames. This leads to decrease the huge computations about motion estimations. This work uses the 1-dimensional degenerated descriptions of each motion image between 2 adjacent frames. Connecting the 1-dimensional degenerated descriptions on time direction, we have the space-time map. This space-time map describes a sequence of frames as a 2-dimensional image. Using this space-time map on motion compensation vector frames and normal color frames, this work shows the method to retrieve a small number of plays in a huge number of frames. Our experiment records 0.93 as recall, 0.81 as precision and 0.86 as F-measure on 139 plays in 132503 frames.