Optimising computer vision based ADAS: vehicle detection case study PROJECT TITLE :Optimising computer vision based ADAS: vehicle detection case studyABSTRACT:Computer vision ways for advanced driver help systems (ADAS) should be developed considering the sturdy necessities imposed by the trade, together with real-time performance in low cost and low consumption hardware (HW), and fast time to promote. These two apparently contradictory needs create the necessity of adopting careful development methodologies. During this study the authors review existing approaches and describe the methodology to optimise computer vision applications without incurring in costly code optimisation or migration into special HW. This approach is exemplified on the enhancements achieved on the successive re-styles of car detection algorithms for monocular systems. Within the experiments the authors observed a ×fifteen speed up between the first and fourth prototypes, progressively optimised using the proposed methodology from the very 1st naive approach to a fine-tuned algorithm. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Energy-efficient dynamic traffic offloading and reconfiguration of networked data centers for big data stream mobile computing: review, challenges, and a case study Measuring the Influence of Perceived Cybercrime Risk on Online Service Avoidance
