Title: Pattern Recognition in Transportation
Abstract: The research, development and design of Intelligent Transportation Systems worldwide relies on technologies that are able to enhance security and safety, increase efficiency, reduce congestion and promote environmental sustainability. In addition, transportation systems are becoming increasingly complex as they are required to deliver mobility to large, diverse and densely populated areas across multiple modes of transportation, e.g. cars, public transport, bicycles, electric cars, etc. Transportation systems able to cope with these challenges and scale will necessarily rely on smart sensors that monitor and act upon stimuli from the environment. Of all sensor options, visual sensors will continue to be a preferred choice since they provide data that humans can easily process and verify, e.g. it is estimated that every vehicle built after 2014 will come equipped with a rear-mounted camera.
As pattern recognition techniques mature, the demand for applications in the transportation domain will only grow. These applications range from automated vehicle detection and access control to safety systems for red-light, lane or speed management passing through traffic condition monitoring, incident detection, autonomous vehicles, etc. We will first take a look at the state-of-the-art of the different solutions with emphasis on those that present open research challenges. We will also take a look at the main trends in transportation in order to understand what research is likely to be of high relevance in future transportation systems.
- First name, Surname: Rodríguez-Serrano, Jose
- Title: PhD, Research Scientist and Project Lead
- Organization: Xerox
- Personal web page: http://www.xrce.xerox.com/Research-Development/Document-Content-Laboratory/Textual-Visual-Pattern-Analysis-TVPA/People/Jose-A-Rodriguez-Serrano
About the author:
Jose A. Rodriguez-Serrano is a Research Scientist at the Xerox Research Centre Europe in the Textual and Visual Pattern Analysis (TVPA) group. His research interests are the application of computer vision and machine learning techniques to transportation and document analysis applications. He has a strong interest in textual images, video analysis, sequential data and image retrieval.
Dr. Rodriguez-Serrano is heavily involved in Xerox’s innovation activities for transportation, acting as a research project lead. With over $800M in revenue, the Transportation Solutions Group is the number one provider of parking, tolling, enforcement and public transportation services to governments worldwide. Dr. Rodriguez-Serrano is part of a team of researchers building and supporting an innovation pipeline that delivers incremental and disruptive growth to the business.
The Xerox Research Centre Europe currently collaborates with over 50 academic and industrial institutions worldwide through a variety of government projects and open innovation initiatives. Some of the key competencies the lab holds are computer vision; analytics and optimization; machine learning; machine translation; natural language processing; parsing and semantics; social and content networks; ethnography; services computing and services economics.
Dr. Rodriguez-Serrano holds a Degree in Physics from the University of Barcelona, a Master in Computer Vision from the Computer Vision Center in Spain, and a PhD in Computer Science from the Autonomous University of Barcelona. In his10 years of experience in innovation he has hold positions in academic research; corporate research; technology transfer; and R&D. He is a member of the PASCAL network of excellence and is the author of several international publications and patents.
Research interest: See above