{"product_id":"computer-vision-for-structural-dynamics-and-health-monitoring","title":"Computer Vision for Structural Dynamics and Health Monitoring","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eThis book provides a comprehensive coverage of theory and hands-on implementation of computer vision-based sensors for structural health monitoring. It offers a complete, state-of-the-art review of the collective experience gained in recent years and explores the potentials of the vision sensor as a fast and cost-effective tool for solving SHM problems. It includes a wide range of tests conducted in controlled laboratory and complex field environments to evaluate the sensor accuracy and demonstrate the unique features and merits of computer vision-based structural displacement measurement. \u003c\/blockquote\u003e\u003cp\u003e                                                            \u003cstrong\u003eFormat\u003c\/strong\u003e: Hardback\u003cbr\u003e                              \u003cstrong\u003eLength\u003c\/strong\u003e: 256 pages\u003cbr\u003e                              \u003cstrong\u003ePublication date\u003c\/strong\u003e: 05 November 2020\u003cbr\u003e                              \u003cstrong\u003ePublisher\u003c\/strong\u003e: John Wiley and Sons Ltd\u003cbr\u003e                          \u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThis comprehensive book bridges the gap between scientific research in computer vision and its practical applications in structural health monitoring (SHM). It offers a thorough and up-to-date review of the collective expertise gained by the SHM community in recent years. Furthermore, it delves into the potential of vision sensors as a fast and cost-effective tool for addressing SHM challenges, leveraging time and frequency domain analytics. By expanding the application of emerging computer vision sensor technology beyond scientific research and into engineering practice, this book contributes significantly to the field.\u003cbr\u003e\u003cbr\u003eComputer Vision for Structural Dynamics and Health Monitoring provides a detailed exploration of critical knowledge, important issues, and practical techniques essential for developing vision-based sensors. It covers robustness in template matching techniques for target tracking, coordinate conversion methods for determining calibration factors, sensing differences between artificial and natural targets, real-time versus post-processing measurements, and field measurement error sources and mitigation methods.\u003cbr\u003e\u003cbr\u003eThe book also includes a wide range of tests conducted in controlled laboratory and complex field environments to evaluate the sensor accuracy and showcase the unique features and advantages of computer vision-based structural displacement measurement.\u003cbr\u003e\u003cbr\u003eBy offering a comprehensive understanding of the principles and applications of computer vision in structural dynamics and health monitoring, this book assists in broadening the application of the emerging computer vision technology in SHM. It serves as a valuable resource for researchers, engineers, and practitioners interested in leveraging computer vision for monitoring and maintaining structural integrity.\u003c\/p\u003e\u003cp\u003e                            \u003cstrong\u003eWeight\u003c\/strong\u003e: 436g                            \u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 158 x 236 x 23 (mm)                            \u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9781119566588                                                      \u003c\/p\u003e","brand":"Dongming Feng,Maria Q. Feng","offers":[{"title":"Hardback","offer_id":44106057220346,"sku":"9781119566588","price":60.96,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/4efd296698af12b228d61ac791575919.jpg?v=1621064165","url":"https:\/\/shulphink.com\/products\/computer-vision-for-structural-dynamics-and-health-monitoring","provider":"Shulph Ink","version":"1.0","type":"link"}