Roadside Video Data Analysis Deep Learning - Verma, Brijesh; Zhang, Ligang; Stockwell, David; SpringerLink (Online service) (Singapore : Springer Nature Singapore : Imprint: Springer, 2017)
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.
Chapter 1: Introduction -- Chapter 2: Roadside Video Data Analysis Framework -- Chapter 3: Non-Deep Learning Techniques for Roadside Video Data Analysis -- Chapter 4: Deep Learning Techniques for Roadside Video Data Analysis -- Chapter 5: Case Study: Roadside Video Data Analysis for Fire Risk Assessment -- Chapter 6: Conclusion and Future Insight - References.
Keywords: Signal processing; Computational intelligence; User interfaces (Computer systems).; Human-computer interaction; Image processing -- Digital techniques; Computer vision; Transportation engineering; Traffic engineering; Signal, Speech and Image Processing; Computational Intelligence; User Interfaces and Human Computer Interaction; Computer Imaging, Vision, Pattern Recognition and Graphics; Transportation Technology and Traffic Engineering