This study tested whether multiple-object tracking-the ability to visually index objects on the basis of their spatiotemporal history-is scene based or image based. Initial experiments showed equivalent tracking accuracy for objects in 2-D and 3-D motion. Subsequent experiments manipulated the speeds of objects independent of the speed of the scene as a whole. Results showed that tracking accur...

The Incremental Focus of Attention (IFA) framework provides a structure in which diierent algorithms for visual motion tracking can be assembled into a single system which tracks an object with the best combination of precision, speed, and robustness. IFA puts diierent tracking algorithms in a hierarchy based on speed and precision and supplies a means for determining which algorithm should per...

Designing a robust tracking control for a non-linear MIMO system with uncertainty is one of the most complicated control problems. In this paper, sliding mode changed to non-linear controllable canonical form by input-output linearization. This, sliding surfaces can be defined in a way that we can de-couple equations and indicate the sliding conditions of multi-variable controller system. The u...

In this paper we discuss about a target tracking algorithm based on Mean Shift and Kalman Filter, which is suitable for high speed moving target tracking. The basic Mean Shift algorithm is described in this paper as well. Although basic Mean Shift algorithm can realize target tracking without arguments or searching all the areas effectively, it has shortcomings which can limit its effectiveness...

Analyzing the traditional visual object recognition algorithm, we presented a complete set of visual target recognition and object tracking algorithm. The algorithm uses image processing method to calculate the frame and characteristic points. And a predictable based on the "search window" approach was given in the algorithm. Experiments have shown that this target tracking algorithm speed up p...