COVERED DISTANCES OF HANDBALL PLAYERS OBTAINED BY AN AUTOMATIC TRACKING METHOD

The aim of this work is to obtain the distances covered by handball players and their velocities during a match using a new approach based on automatic tracking method described in Figueroa et. al. (2006a, 2006b) and the Adaboost detector (Okuma, 2004). A whole game of a Brazilian regional handball championship for players under age of 21 was recorded. Applying the mentioned automatic tracking, the accumulated covered distances and the velocities were calculated for all the players. The results of average covered distances (±SD) in the 1st and 2 nd halves were 2199(±230) and 2453(±214). The results of covered distances and the velocities allow individual and collective analyses of the players by the team staff. The proposed method revealed to be a powerful tool to improve physical analysis of the handball players

Measuring Handball Players Trajectories Using An Automatically Trained Boosting Algorithm.

The aim of the present paper is to propose and evaluate an automatically trained cascaded boosting detector algorithm based on morphological segmentation for tracking handball players. The proposed method was able to detect correctly 84% of players when applied to the second period of that same game used for training and 74% when applied to a different game. Furthermore, the analysis of the automatic training using boosting detector revealed general results such as the training time initially increased with the number of figures used, but as more figures were added, the training time decreased. Automatic morphological segmentation has shown to be a fast and efficient method for selecting image regions for the boosting detector and allowed an improvement in the automatic tracking of handball players.1453-6