Pascual J. Figueroa

A flexible software for tracking of markers used in human motion analysis

In this work, we present a software for the tracking of markers used in human motion analysis. This software is based mainly on image sequences captured by video cameras and on image processing and computer vision tools. Unlike the optoelectronic systems, which record only the coordinates of the markers, a video-based system offers more visual information and flexibility which can be exploited in different applications. However, it needs a more complex tracking procedure concerned with the extraction and identification of the used markers. The tracking module presented here is divided into the following three procedures: segmentation, matching and prediction. The segmentation consists in extracting the objects of interest (markers). The matching is used to find the correspondence between the extracted objects in two consecutive frames. The prediction is important to limit the region of processing, thus reducing the execution time. Some results of the automatic tracking are presented together with their application in human motions analysis.

Tracking soccer players aiming their kinematical motion analysis

In this work, we consider the problem of tracking players, during a soccer game, through the use of multiple cameras. The main goal here consists in finding the position of the players on the pitch at each instance of time. The tracking is performed through a graph representation in which the nodes correspond to the blobs obtained by image segmentation and the edges, weighted using the blobs information and trajectory in the image sequence, represent the distance between nodes. We present a new way of trating occlusions by splitting segmented blobs based on morphological operators and a backward and forward graph representation which allows an increasing in the number of frames automatically tracked. Unlike other works in which the analysis of short video sequences is presented, this paper illustrates the tracking results for all the players during a whole game.

Tracking soccer players using the graph representation

In this work, we consider the problem of tracking soccer players during a game by using multiple cameras. The main goal consists in finding the position of the players on the pitch at each instance of time. The occlusion is treated by splitting segmented blobs and the tracking is performed using a graph representation, where nodes correspond to the blobs obtained by image segmentation and edges represent the distance between the blobs.

Background recovering in outdoor image sequences: An example of soccer players segmentation

In this work, we consider the problem of background pixels information recovering which can be used, for example, in applications concerning segmentation and tracking of components in video images. Shortly, to recover the background of image sequences representing outdoor scenes, we consider a non-parametric morphological leveling operation, which takes into account the specific problem of lighting changes and the fact that we can have both slow and fast motion in the scene. We illustrate the segmentation of players based on the difference between image sequences and the corresponding recovered background representation. We also discuss the reduction of shadows in digital video of soccer games and show the good results of the whole background recovering and segmentation process.