摘要：AbstractReal world objects are recognized by tracking less and tracking based techniques. Mobile augmented reality browsers are tracking less systems, which acquires location data using global positioning system and provide information in the form of maps or web links. Tracking based techniques recognize objects through markers or directly real world objects without markers. Marker based systems actually track the markers not the real objects and therefore, these approaches hides the reality. Marker- less (direct real object tracking) systems use client-server architecture. However, these are affected by network latency. The Smartphone is capable to recognize and track real world objects without any server and marker. It can guide the users about their location and also provide information in a convenient way. Therefore, an improved algorithm for tracking real world objects through natural features was formulated. The modified version of speed up robust features (SURF) was used for features extraction from live mobile camera image and recognition. The pose matrix from extracted features was calculated by Homography. The adapted algorithm was tested in a mobile AR-prototype application using iPhone. It was found from the results that the formulated algorithm recognized and tracked the real world objects from natural features in speedy, easy and convenient way
