Abstract
In the last years 3D-Vision systems based on the Time-Of-Flight (TOF) principle have gained more importance than Stereo Vision (SV). TOF offers a direct depth-data acquisition, whereas SV involves a great amount of computational power for a comparable 3D data set. Due to the enormous progress in TOF-techniques, nowadays 3D cameras can be manufactured and be used for many practical applications. Hence there is a great demand for new accurate algorithms for 3D object recognition and classification. This paper presents a new strategy and algorithm designed for a fast and solid object classification. A challenging example - accurate classification of a (half-) sphere - demonstrates the performance of the developed algorithm. Finally, the transition from a general model of the system to specific applications such as Intelligent Airbag Control and Robot Assistance in Surgery are introduced. The paper concludes with the current research results in the above mentioned fields.
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.
