This paper proposes a method for offline accurate ball tracking for short volleyball actions in sport halls. Our aim is to detect block touches on the ball and to determinate accurate trajectory and impact positions of the ball to support referees. The proposed method is divided into two stages, namely training and ball tracking, and is based on background subtraction. Application of the Gaussian mixture model has been used to estimate a background, and a high-speed camera with a capture rate of 180 frames per second and a resolution of 1920 × 1080 are used for motion capture. In sport halls significant differences in light intensity occur between each sequence frame. To minimize the influence of these light changes, an additional model is created and template matching is used for accurate determination of ball positions when the ball contour in the foreground image is distorted. We show that this algorithm is more accurate than other methods used in similar systems. Our light intensity change model eliminates almost all pixels added to images of moving objects owing to sudden changes in intensity. The average accuracy achieved in the validation process is of 0.57 pixel. Our algorithm accurately determined 99.8% of all ball positions from 2000 test frames, with 25.4 ms being the average time for a single frame analysis. The algorithm presented in this paper is the first stage of referee support using a system of many cameras and 3D trajectories.

The policy set by the European Commission for Programming Period 2014–2020 introduced new instruments supporting regional development but also posed new requirements that must be met by European regions. One of them is smart specialization. To implement Strategy for Europe 2020, published by the European Commission in 2010, EU Member States and their regions develop strategies for smart specialization that show directions for providing support to the strengthening of research, development and innovation. Smart specialization is an important instrument for strengthening of competitiveness as well as for defining and building the knowledge-based economy. This article presents analysis of processes responsible for identifying smart specialization in Pomeranian and West Pomeranian Regions (in Polish: Voivodeships). This analysis is a continuation and extension of the research on the process of emergence of smart specialization in Pomeranian Region by the inclusion of the West Pomeranian Region into this study. Both Regions are situated on the southern coast of the Baltic Sea and are seats of main Polish harbours and shipyards. Their regional capitals Gdańsk and Szczecin are the cores of emerging metropolitan areas. The aims of the article are: (1) assessment of methods of smart specialization emergence and selection; (2) analysis of differences and similarities of areas of smart specialization of two coastal regions. In Pomeranian region the process of emergence of smart specialization was a bottom-up one where the Regional Government organized the competition and invited actors to build partnerships. In other regions of Poland it was more of a top-down process, but with participation of stakeholders. The West Pomeranian Region is an example of this approach. Methods of the research applied for this study include: analysis of literature, documents from Voivodeship Marshal Offices, individual interviews, participation in the process of emerging of smart specialization in Pomeranian Voivodeship and comparative analysis of the methods of their emergence in both regions.