Roadside Video Data Analysis Deep Learning /

• Main Authors: Verma, Brijesh (Author), Zhang, Ligang (Author), Stockwell, David (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Singapore : Springer Singapore : Imprint: Springer, 2017.
• Series: Studies in Computational Intelligence, 711
• Subjects: Engineering.; User interfaces (Computer systems).; Computer graphics.; Computational intelligence.; Transportation engineering.; Traffic engineering.; Signal, Image and Speech Processing.; Computational Intelligence.; User Interfaces and Human Computer Interaction.; Computer Imaging, Vision, Pattern Recognition and Graphics.; Transportation Technology and Traffic Engineering.
• Physical Description: XXV, 189 p. 79 illus., 68 illus. in color. online resource.
• ISBN: 9789811045394
• ISSN: 1860-949X ;

This book highlights the methods and applications for roadside video data analysis, with a particular focus on the use of deep learning to solve roadside video data segmentation and classification problems. It describes system architectures and methodologies that are specifically built upon learning concepts for roadside video data processing, and offers a detailed analysis of the segmentation, feature extraction and classification processes. Lastly, it demonstrates the applications of roadside video data analysis including scene labelling, roadside vegetation classification and vegetation biomass estimation in fire risk assessment.