opticalflow

所属分类:Windows编程
开发工具:Visual C++
文件大小:14KB
下载次数:32
上传日期:2006-04-27 09:17:11
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说明:  this program, opticalflow.c, is an implementation of Uras et al. 1988 s motion
(this program, opticalflow.c. is an implementation of Uras et al. 1,988 s motion)

文件列表:
opticalflow (0, 2006-04-27)
opticalflow\makeuras.txt (79, 2005-05-23)
opticalflow\uras.c (68510, 2005-05-23)

This README written by Steven Beauchemin This program, uras.c, is an implementation of Uras et al. 1***8's motion detection algorithm. To compile: make -f makeuras Everything is in a single file so a make is really not necessary but... This program uses a sequence of input images and smooths them according to the sigma values provided by the user prior to the estimation of the optical flow using a 2nd-order derivative technique. Derivatives are computed using 4-point central difference masks. Examples of run files are also present. (You'll have to change the directory names where the input and output are directed.) Here's a description of a typical command line (that is exactly what one gets if one invokes the program with no parameters): Usage: uras input-path output-path seq-name. [-SG n.n] [-TG n.n] [-M n] [-R 1 | -R 2 n.n] [-B rows cols] [-F n.n] [-C corr-vel-file -T1 nbins1 increment1 -T2 nbins2 increment2] [-SG n.n] : sigma value for spatial gaussian default value is 3.0 [-TG n.n] : sigma value for temporal gaussian default value is 1.5 [-M n] : middle frame of image sequence default value is 0 [-R 1 | -R 2 n.n] : n = 1 : applies TR1 regularization n = 2 : applies TR2 regularization with sigma = n.n [-B rows cols] : for binary input files without header [-F n.n] : filters out unreliable estimates using the Gaussian curv. (det(H)) [-C corr-vel-file -T1 nbins1 increment1 -T2 nbins2 increment2] : error histogram corr-vel-file : file of correct velocities nbins1, nbins2 : number of bins for histogram increnent1, increment2 : value of gap between bins Here is a typical run: uras /data/images1/BURKITT/testdata /data/images1/BURKITT/outdata treet. -SG 3.0 -TG 1.5 -M 9 -R 1 -F 0.5 -C correct_treet -T1 20 0.5 -T2 20 0.5 This command means: run uras using the input files from /data/images1/BURKITT/testdata and put output files in /data/images1/BURKITT/outdata treet. is the stem name of a typical set of input images (for example, the complete filename for frame 9 is "treet.9"). In the above example, the program expects to find the input images in /data/images1/BURKITT/testdata. -SG 3.0 indicates that the sigma value of the spatial smoothing of the image sequence is 3.0 -TG 1.5 indicates that the sigma value of the temporal smoothing of the image sequence is 1.5 (the program computes the required number of frames by itself, see option -M) -M 9 indicates that the flow field will be estimated for frame 9, the program will automatically read in the required number of frames on both sides of frame 9, according to the sigma value of temporal smoothing given by -TG and the size of the derivative masks -R 1 indicates that regularization procedure TR1 is used (see Uras et al.'s paper). -R 2 n.n indicates that procedure TR2 is used (we did not use it in our study). n.n is the sigma value of the spatial smoothing of the computed flow field when using TR2 -C indicates the correct answer is available and that you want error analysis conducted and that data is in /data/images1/BURKITT/testdata/correct_treet (change this as well as appropriate). The data is analysed by producing 2 histograms. -T1 and -T2 are mandatory when using -C. They specify the number of bins the histogram will contain and the increment between them. The histograms are constructed by considering the error of the estimates versus the confidence measure det(H) and the condition number of the matrix H. -F n.n allows the user to preserve the estimates that show det(H) >= n.n only. The program automatically generates the output filenames for the flow field and the histogram (if an histogram is requested). For the above example, the filename of the flow field would be: uras.treet.F-sg3.0-tg1.5-m9-r1-f0.5 and the filename of the histogram: uras.treet.H-sg3.0-tg1.5-m9-r1-f0.5 Note that the letters and numbers of the extension are the parameters used when invoking the program. The program takes between 0:30 and 4:00 minutes to run on an IBM 6000, depending on the size of the images being processed. See the README for information about the output format for flows and use software in ../SOFTWARE to print out the flow fields in postscript.

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