By Ahmed El-Rafei, Tobias Engelhorn (auth.), João Manuel R. S. Tavares, R. M. Natal Jorge (eds.)
This e-book comprises prolonged types of papers offered on the overseas convention VIPIMAGE 2009 – ECCOMAS Thematic convention on Computational imaginative and prescient and scientific snapshot, that was once held at Faculdade de Engenharia da Universidade do Porto, Portugal, from 14th to sixteenth of October 2009. This convention was once the second one ECCOMAS thematic convention on computational imaginative and prescient and clinical snapshot processing. It lined themes relating to photograph processing and research, scientific imaging and computational modelling and simulation, contemplating their multidisciplinary nature. The publication collects the state of the art learn, equipment and new tendencies near to computational imaginative and prescient and scientific picture processing contributing to the advance of those wisdom areas.
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Extra resources for Computational Vision and Medical Image Processing: Recent Trends
Although in reality the set of sections belong to the same player the tracking algorithm sees each portion as belonging to a different player. 3). Figure 11 and Table 2 represent the data for player B. 2 s later the player was not detected for a long enough period and his track was lost. During this sample footage the tracking algorithm lost the player three times. We could achieve better results on player C as shown on Fig. 12 and Table 3. The tracking algorithm only lost the player two times and on the second section it was able to follow the player during 30 s.
1, pp. 93–102. Manchester, UK (2001) ˇ 9. : Position related differences in volume and intensity of large scale cyclic movements of male players in handball. Kinesiology 36(1), 58–68 (2004) 10. Sousa, A: Arquitecturas de Sistemas Rob´oticos e Localizac¸a˜ o em Tempo Real Atrav´es de Vis˜ao. Feup Edic¸o˜ es, Porto, Portugal (2003) 11. : Vision based real-time localization of multiple mobile robots. In: 3rd International Conference on Field and Service Robotics, pp. 103–106. Helsinki, Finland (2001) 12.
M and N is the size of the template. k and l are offsets for matching at different position. E. Constantinou et al. The template for the matching the following image frames is then updated according to Eq. (2) and the matching procedure is repeated until the last image frame. i / is the matched position of the symphysis pubis in image frame i . A similar adaptive matching algorithm is used to track the motion of ARA. However, ARA is a soft tissue structure which deforms, particularly in fast maneuvers like coughing.
Computational Vision and Medical Image Processing: Recent Trends by Ahmed El-Rafei, Tobias Engelhorn (auth.), João Manuel R. S. Tavares, R. M. Natal Jorge (eds.)