7、This paper presents a new method for estimating dense and accurate optical flow based on the motion of planar regions.
11、The factors, which introduce the error of temporal differential estimation are, analyzed. The successive approximation calculation model for the optical flow estimation is put forward.
15、The experimental results show that this method has the advantages of robustness, global optimality and high convergent speed and it is feasible for optical flow estimation of nonrigid body.
2、Moreover, block matching algorithm is the better one in the computational methods of optical flow.
6、Motion object detection based on optical flow field and level set
12、Calculation of optical flow of an algorithm, which is an algorithm for the time being, I hope to do this more than friends advice.
17、In this paper a genetic algorithm (GA) based method for optical flow estimation of nonrigid object is presented. The nonrigid body is divided into several infinitesimal patches in which the pixels move together. The motion parameters of the patches are optimally estimated using GA method.
5、It is also commonly referred to as optical flow computation especially in the computer vision literature.
13、I described a point correspondence algorithm in the text, the algorithm combined two methods, optical flow and color density distribution, it also took advantages of them.
3、L-K optical flow algorithm is not very suitable in facial feature point tracking.
10、A new model based global motion estimation method is proposed by fitting optical flow field for aerial video imagery.
4、In order to get the motion parameters of the moving object, optical flow method is introduced.
16、In this paper, a facial feature point tracking scheme is proposed by integrating Lucas-Kanade optical flow tracking algorithm and the face alignment statistical model, DAM (direct appearance model), together in a Bayesian framework.
14、However, the error of the optical flow estimation derived from the error of temporal differential estimation is not taken into account in above methods.
1、Calculation of optical flow is based on gradient method.
9、If combined with optical flow computing, this algorithm can highly reduce the computation amounts and enhance the computing rate.
8、A new ellipse-tracking algorithm based on the active contour and the optical flow technique was proposed.
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