TY - BOOK ID - 8135143 TI - Big Visual Data Analysis : Scene Classification and Geometric Labeling AU - Chen, Chen. AU - Ren, Yuzhuo. AU - Kuo, C.-C. Jay. PY - 2016 SN - 9811006296 9811006318 PB - Singapore : Springer Singapore : Imprint: Springer, DB - UniCat KW - Applied Physics KW - Electrical Engineering KW - Telecommunications KW - Engineering & Applied Sciences KW - Electrical & Computer Engineering KW - Computer vision. KW - Geometry. KW - Machine vision KW - Vision, Computer KW - Artificial intelligence KW - Image processing KW - Pattern recognition systems KW - Mathematics KW - Euclid's Elements KW - Visualization. KW - Signal, Image and Speech Processing. KW - Image Processing and Computer Vision. KW - Visualisation KW - Imagination KW - Visual perception KW - Imagery (Psychology) KW - Signal processing. KW - Image processing. KW - Speech processing systems. KW - Optical data processing. KW - Mathematics. KW - Math KW - Science KW - Optical computing KW - Visual data processing KW - Bionics KW - Electronic data processing KW - Integrated optics KW - Photonics KW - Computers KW - Computational linguistics KW - Electronic systems KW - Information theory KW - Modulation theory KW - Oral communication KW - Speech KW - Telecommunication KW - Singing voice synthesizers KW - Pictorial data processing KW - Picture processing KW - Processing, Image KW - Imaging systems KW - Optical data processing KW - Processing, Signal KW - Information measurement KW - Signal theory (Telecommunication) KW - Optical equipment UR - https://www.unicat.be/uniCat?func=search&query=sysid:8135143 AB - This book offers an overview of traditional big visual data analysis approaches and provides state-of-the-art solutions for several scene comprehension problems, indoor/outdoor classification, outdoor scene classification, and outdoor scene layout estimation. It is illustrated with numerous natural and synthetic color images, and extensive statistical analysis is provided to help readers visualize big visual data distribution and the associated problems. Although there has been some research on big visual data analysis, little work has been published on big image data distribution analysis using the modern statistical approach described in this book. By presenting a complete methodology on big visual data analysis with three illustrative scene comprehension problems, it provides a generic framework that can be applied to other big visual data analysis tasks. ER -