Dimitris Metaxas – författare

Edward Muybridge (1830–1904) is known as the pioneer in motion capt- ing with his famous experiments in 1887 called “Animal Locomotion”. Since then, the ?eld of animal or human motion analysis has grown in many dir- tions. However, research and results that involve human-like animation and the recovery of motion is still far from being satisfactory. The modelling, tracking, and understanding of human motion based on video sequences as a research ?eld has increased in importance particularly in thelastdecadewiththeemergenceofapplicationsinsportssciences,medicine, biomechanics, animation (online games), surveillance, and security. Progress in human motion analysis depends on empirically anchored and grounded research in computer vision, computer graphics, and biomechanics. Though these ?elds of research are often treated separately, human motion analysis requires the integration of methodologies from computer vision and computer graphics.Furthermore,theunderstandinganduseofbiomechanicsconstraints improves the robustness of such an approach. This book is based on a June 2006 workshop held in Dagstuhl, Germany. This workshop brought together for the ?rst time researchers from the afo- mentioned disciplines. Based on their diverse perspectives, these researchers havebeendevelopingnewmethodologiesandcontributing,throughtheir?- ings, to the domain of human motion analysis. The interdisciplinary character of the workshop allowed people to present a wide range of approaches that helped stimulate intellectual discussions and the exchange of new ideas.

This book constitutes the refereed proceedings of the 5th International Conference on Dynamic Data Driven Applications Systems, DDDAS/Infosymbiotics for Reliable AI 2024, held in New Brunswick, NJ, USA, during November 6–8, 2024.The 43 full papers included in this book were carefully reviewed and selected from 52 submissions. By combining DDDAS and typical AI approaches, the papers address state-of-the-art efforts to create frameworks for enabling new and advanced Science and Technology capabilities to address challenges and create opportunities in important areas, spanning a wide set of areas, such as: materials and aerospace systems; communications networks; energy infrastructures; cyber-security; adverse environmental situations; societal dynamics; computer vision; robotics; laboratory automation; bio-informatics and pharmaceuticals design; and more.

This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Medical Computer Vision: Algorithms for Big Data, MCV 2014, held in Cambridge, MA, USA, in September 2019, in conjunction with the 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014.

This book constitutes the thoroughly refereed prost-workshop proceedings of the International Workshop on Medical Computer Vision: Algorithms for Big Data, MCS 2015, held in Munich, Germany, in October 2015, held in conjunction with the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015.The workshop shows well the current trends and tendencies in medical computer vision and how the techniques can be used in clinical work and on large data sets. It is organized in the following sections: predicting disease; atlas exploitation and avoidance; machine learning based analyses; advanced methods for image analysis; poster sessions. The 10 full, 5 short, 1 invited papers and one overview paper presented in this volume were carefully reviewed and selected from 22 submissions.

This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Medical Computer Vision, MCV 2016, and of the International Workshop on Bayesian and grAphical Models for Biomedical Imaging, BAMBI 2016, held in Athens, Greece, in October 2016, held in conjunction with the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016.The 13 papers presented in MCV workshop and the 6 papers presented in BAMBI workshop were carefully reviewed and selected from numerous submissions.The goal of the MCV workshop is to explore the use of "big data” algorithms for harvesting, organizing and learning from large-scale medical imaging data sets and for general-purpose automatic understanding of medical images.The BAMBI workshop aims to highlight the potential of using Bayesian or random field graphical models for advancing research in biomedical image analysis.

This book constitutes the refereed proceedings of the International Symposium on Medical Simulation, ISMS 2004, held in Cambridge, MA, USA in June 2004. The 32 revised full papers presented were carefully reviewed and selected from 50 submissions. The papers are organized in topical sections on soft tissue properties and modeling, real-time deformable models, haptic rendering, anatomical modeling, and applications and development frameworks.