Mean shift algorithm based on fusion model for head tracking

To solve the mismatch between the candidate model and the reference model caused by the time change of the tracked head, a novel mean shift algorithm based on a fusion model is provided. A fusion model is employed to describe the tracked head by sampling the models of the fore-head and the back-head under different situations. Thus the fusion head reference model is represented by the color distribution estimated from both the fore- head and the back-head. The proposed tracking system is efficient and it is easy to realize the goal of continual tracking of the head by using the fusion model. The results show that the new tracker is robust up to a 360°rotation of the head on a cluttered background and the tracking precision is improved.

Tracking of human head with particle filter

To cope with the problem of tracking a human head in a complicated scene,we propose a method that adopts human skin color and hair color integrated with a kind of particle filter named condensation algorithm.Firstly,a novel method is presented to set up human head color model using skin color and hair color separately based on region growing.Compared with traditional human face model,this method is more precise and works well when human turns around and the face disappears in the image.Then a novel method is presented to use color model in condensation algorithm more effectively.In this method,a combination of edge detection result,color segmentation result and color edge detection result in an Omega window is used to measure the scale and position of human head in condensation.Experiments show that this approach can track human head in complicated scene even when human turns around or the distance of tracking a human head changes quickly.

Application of Predictive Algorithm in Head-Tracking System

The worldwide research status of head tracking is introduced and the works made in the research of the predictive algorithm and in the exploration of the rule of the head tracking are set forth. A time delay model for the telerobotic scout system is built. In respect of eliminating error caused by time delay and making reasonable prediction to the data stream, many methods are experimented in order to realize the aim of real time tracking. The application of extrapolation algorithm and auto recursive algorithm in the orientation tracking is described in detail. These two algorithms are realized in Matlab environment. Through analysis of the curves generated by using these two predictive algorithms, an appropriate method was applied in the telerobotic scout system. The effect is satisfying.

Command Filtered Finite/Fixed-time Heading Tracking Control of Surface Vehicles

This paper investigates the heading tracking problem of surface vehicles with unknown model parameters.Based on finite/fixed-time control theories and in the context of command filtered control,two novel adaptive control laws are developed by which the vehicle can track the desired heading within settling time with all signals of the closed-loop system are uniformly bounded.The effectiveness and performance of the schemes are demonstrated by simulations and comparison studies.

Precise perception of virtual object position in real world

There is a deviation between actual and theoretical perceived positions of virtual object in stereoscop-ic display.Therefore,methods for precise position perception in real world are proposed in this paper.The causes for the deviation are analyzed on the basis of geometrical optics .Then deviation correctionsare performed by error compensation with mathematic method and by remodeling virtual viewpoint dynami-cally with the movement of physical viewpoint.Experimental results show that these methods can reducethe position deviation to less than 10 millimeter,meeting the requirements for direct manipulation in mul-ti-sensory virtual environment.