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Real-Time Vision for Human-Computer Interaction
The need for natural and effective Human-Computer Interaction (HCI) is increasingly important due to the prevalence of computers in human activities. Computer vision and pattern recognition continue to play a dominant role in the HCI realm. However, computer vision methods often fail to become pervasive in the field due to the lack of real-time, robust algorithms, and novel and convincing applications. This state-of-the-art contributed volume is comprised of articles by prominent experts in computer vision, pattern recognition and HCI. It is the first published text to capture the latest research in this rapidly advancing field with exclusive focus on real-time algorithms and practical applications in diverse and numerous industries, and it outlines further challenges in these areas. Real-Time Vision for Human-Computer Interaction is an invaluable reference for HCI researchers in both academia and industry, and a useful supplement for advanced-level courses in HCI and Computer Vision.
Mathematics for Human Flourishing in the Time of COVID-19 and Post COVID-19
The International Chair in Mathematical Physics and Applications (ICMPA - UNESCO chair), University of Abomey-Calavi, Benin, and the Center for Applied Mathematics of the Faculty of Mechanical Engineering Niš, CAM-FMEN, organized a webinar on Mathematics for human flourishing in the time of COVID-19 and post COVID-19, 21 October 2020, supported by the City of Niš. The objectives of the webinar were to give precise information about the work that scientists do to cure the disease, to push forward technology, to understand our society and create new expressions of humanity, and to question the role of mathematics in the responses to this pandemic.
Applied Graph Theory in Computer Vision and Pattern Recognition
This book presents novel graph-theoretic methods for complex computer vision and pattern recognition tasks. It presents the application of graph theory to low-level processing of digital images, presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, and provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks.
Animal and Plant Stem Cells
This book provides a multifaceted look into the world of stem cells and explains the similarities and differences between plant and human stem cells. It explores the intersection between animals and plants and explains their cooperative role in bioengineering studies. The book treats both theoretical and practical aspects of stem cell research. It covers the advantages and limitations of many common applications related to stem cells: their sources, categories, engineering of these cells, reprogramming of their functions, and their role as novel cellular therapeutic approach. Written by experts in the field, the book focuses on aspects of stem cells ranging from expansion-propagation to meta...
Computer Vision -- ECCV 2014
The seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed proceedings of the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014. The 363 revised papers presented were carefully reviewed and selected from 1444 submissions. The papers are organized in topical sections on tracking and activity recognition; recognition; learning and inference; structure from motion and feature matching; computational photography and low-level vision; vision; segmentation and saliency; context and 3D scenes; motion and 3D scene analysis; and poster sessions.
Computer Vision – ECCV 2016
The eight-volume set comprising LNCS volumes 9905-9912 constitutes the refereed proceedings of the 14th European Conference on Computer Vision, ECCV 2016, held in Amsterdam, The Netherlands, in October 2016. The 415 revised papers presented were carefully reviewed and selected from 1480 submissions. The papers cover all aspects of computer vision and pattern recognition such as 3D computer vision; computational photography, sensing and display; face and gesture; low-level vision and image processing; motion and tracking; optimization methods; physics-based vision, photometry and shape-from-X; recognition: detection, categorization, indexing, matching; segmentation, grouping and shape representation; statistical methods and learning; video: events, activities and surveillance; applications. They are organized in topical sections on detection, recognition and retrieval; scene understanding; optimization; image and video processing; learning; action, activity and tracking; 3D; and 9 poster sessions.
