Biomedical subjects

Stanislav Kovacic

Publications and source records attributed to Stanislav Kovacic.

3 recordsLinked to original sources

PubMed2006

Symmetric image registration.

This paper presents an original non-rigid image registration approach, which tends to improve the registration by establishing a symmetric image interdependence. In order to gather more information about the image transformation it measures the image similarity in both registration directions. The presented solution is based on the interaction between the images involved in the registration process. Images interact through forces, which according to Newton's action-reaction law form a symmetric relationship. These forces may transform both of the images, although in our implementation one of the images remains fixed. The experiments performed to demonstrate the advantages of the symmetric registration approach involve the registration of simple objects, the recovery of synthetic deformation, and the inter-patient registration of real images of the head. The results show that the symmetric approach improves both the registration consistency and the registration correctness.

Algorithms↗

PubMed2004

Robust and efficient vision system for group of cooperating mobile robots with application to soccer robots.

In this paper a global vision scheme for estimation of positions and orientations of mobile robots is presented. It is applied to robot soccer application which is a fast dynamic game and therefore needs an efficient and robust vision system implemented. General applicability of the vision system can be found in other robot applications such as mobile transport robots in production, warehouses, attendant robots, fast vision tracking of targets of interest and entertainment robotics. Basic operation of the vision system is divided into two steps. In the first, the incoming image is scanned and pixels are classified into a finite number of classes. At the same time, a segmentation algorithm is used to find corresponding regions belonging to one of the classes. In the second step, all the regions are examined. Selection of the ones that are a part of the observed object is made by means of simple logic procedures. The novelty is focused on optimization of the processing time needed to finish the estimation of possible object positions. Better results of the vision system are achieved by implementing camera calibration and shading correction algorithm. The former corrects camera lens distortion, while the latter increases robustness to irregular illumination conditions.

Algorithms↗

PubMed2002

Observation and analysis of large-scale human motion.

Many team sports include complex human movement, which can be observed at different levels of detail. Some aspects of the athlete's motion can be studied in detail using commercially available high-speed, high-accuracy biomechanical measurement systems. However, due to their limitations, these devices are not appropriate for studying large-scale motion during a game (for example, the motion of a player running across the entire playing field). We describe an alternative approach to studying such large-scale motion, and present a video-based, computer-aided system, developed specifically for the purpose of acquiring large-scale motion data. The baseline of our approach consists of sacrificing much of the spatial accuracy and temporal resolution of widely used biomechanical measurement systems, to obtain data on human movement that span large areas and long intervals of time. Data can be obtained for each of the observed athletes with reasonable amount of operator work. The system was developed using the recordings of a handball match. Several field tests were performed to assess measurement error, including comparison to one of the widely available biomechanical measurement systems. With the help of the system presented, we could obtain position data for all 14 handball players on a 40 x 20 m large court with RMS error better than 0.6 m, covering 1 h of action. Several results, obtained during the handball match study are presented, in order to highlight the importance of large-scale motion acquisition.

Biomechanical Phenomena↗