Abstract
Due to the development of image processing over the last years, the application of vision systems and image recognition technologies has been increasingly applied in many fields. In this paper, Machine Learning and Principal Component Analysis are utilized for context awareness at a smart mobility platform. The restrictions concern a rather dynamic environment and a relevantly small dataset of images. The aim is to determine the position of the camera itself and the appearance of obstacles within a predefined area. To examine the performance of the proposed approach Hierarchical Cluster Analysis has been applied to group similar observations into clusters.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
