Abstract
Video segmentation is one of the most important parts of a vision system which allows partitioning each frame into homogeneous regions that share a common property. This work proposes a new methodology that aggregates three different techniques: background subtraction, region growing and a pseudo Fuzzy colour model to define colour subspaces that characterize each class. In addition, the pseudo Fuzzy colour model allows a given colour to belong to more than one class and enables the expansion ofthe classes through a dynamic model based on belonging and persistence information. In case of shared colours among classes, regional features are searched in order to determine the object's class. Tests with test and real videos of sports footages show promising results.

Abstract
In recent years there has been a growing interest by the sport's experts (teachers and coaches) in developing automatic systems for detecting, tracking and identifying player's movements with the purpose of improving the players' performance and accomplishing a consistent and standard analysis of the game metrics. A challenge like this requires sophisticated techniques from the areas of image processing and artificial intelligence. The objective of our work is to study and develop hardware and software techniques in order to build an automatic visual system for detecting and tracking players in indoor sports games that can aid coaches to analyse and improve the players' perfoiniance. Our methodology is based on colour features and therefore several colour image processing techniques such as background subtraction, blob colour definition (RGB and HSL colour spaces) and colour blob manipulation are employed in order to detect the players. Past information and players' velocity allow the tracking algorithm to define probable areas. Tests conducted with a single IP surveillance camera on the sports hall of the Faculty of Sports from the University of Porto showed detection rates from 72.2% to 93.3%.

Abstract
Recent years have brought an increasing interest on analyzing efficiently the performance of sports players during training sessions and games. The information collected from such analysis is very valuable to educators and coaches since it allows them to better understand the difficulties of a trainee, a player or even an entire team and formulate adequate training and strategic plans accordingly. In order to perform this analysis in a consistent and systematic way, sophisticated sensory systems and data processing techniques are needed. This paper presents a survey on relevant work, current techniques and trends on the area of team tracking systems applied to sports. We propose a classification of these systems by distinguishing them into two main categories: intrusive and nonintrusive. Nonintrusive systems are further refined into outdoor and indoor sports applications. The specific characteristics of each system are itemized, including the identification of the strong points and limitations. Finally, the paper highlights some open issues and research opportunities on this area. © 2010 IEEE.

Abstract
We propose an online sensorimotor architecture for controlling a low-cost humanoid robot to perform dance movements synchronized with musical stimuli. The proposed architecture attempts to overcome the robot's motor constraints by adjusting the velocity of its actuators and inter-changing the attended beat metrical-level on-the-fly. Moreover, we propose quantitative metrics for measuring the level of beat-synchrony of the generated robot dancing motion and complement them with a qualitative survey about several aspects of the demonstrated robot dance performances. Tests with different dance movements and musical pieces demonstrated satisfactory beat-synchrony results despite the physical limitations of the robot. The comparison against robot dance sequences generated without inter-changing the attended metrical-level validated our sensorimotor approach for controlling beat-synchronous robot dancing motions using different dance movements and facing distinct musical tempo conditions.

Abstract
Humanoid robots usually have a large number of degrees of freedom which turns humanoid control into a very complex problem. Humanoids are used in several RoboCup soccer leagues. In this work, the SimSpark simulator of the Simulation 3D will be used. This paper presents an automatic approach for developing humanoid behaviors based on the development of a generic optimization system. The paper describes the adopted architecture, main design choices and the results achieved with the optimization of a side kick and a forward kick. For both skills, the optimization approach allowed the creation of faster and more powerful and stable behaviors.

Abstract
This paper presents a system that is able to control in real time a humanoid robot to perform dance movements to the rhythm of a music. The movements' coordination is performed with the aid of a music analyzer that estimates the beat of the music and calculates a prediction of the next inter-beat-interval (IBI). During the robot dancing performance, a dance movement is chosen from a pre-defined dance library and is executed on-the-fly by the robot. The movements' velocity, as well as the attended metrical-level, are adjusted in real time so that the movement can be executed within the time interval of two beats, and at the same time taking into consideration the robot motor-rates limitations. Results evince a good synchrony of the movement towards the analyzed rhythm, but points to the need of a careful design of the dance movements so they can be naturally executed on time.