Comments (8)
ethan-li-coding
commented on July 29, 2024
- 可以GPU加速，原文就是以GPU算法来介绍的。能否实时计算要看你的计算性能、图像大小以及视差范围，建议在原文中查看它的实验设备和处理速度，然后按比例计算你的数据大概能够达到的水平，时间复杂度大约为O(WHD)。
- 虽然效果有区分，但理论上视差精度不会有优劣之分，他们都是用同样的子像素方法，可能局部会由于处理算法的不适应性导致结果偏移，实际工程应用时建议去掉所有视差填充步骤，只保留一致性检查（AD-Census里叫OutDetection）。在本算法里将参数do_lr_check设置为true，do_filling设置为false。
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laidongd
commented on July 29, 2024
谢谢您的耐心解答.对立体匹配的研究现状不够了解,看论文匹配的效果好像都还不错,但实际跑自己的图片效果却一般,作为门外汉,能否再请教您两个问题:
1.如果要在类似TX2平台实时跑双目匹配,现有的开源算法里面哪个效果会好些,能否推荐一个.
2.在sgm或者AD-Census的结果上继续进行滤波处理,是否会有更好的结果,有没有较好的滤波算法的papper推荐,opensource的就更好了.
谢谢您.
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ethan-li-coding
commented on July 29, 2024
- 限于TX2的性能，还是SGM比较适合，这个算法速度可以加速到非常快，AD-Census相比SGM效果好一些，但是同样在TX2上实现效率可能会有两倍以上的差别。
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ethan-li-coding
commented on July 29, 2024
- 建议先去掉视差填充，把去除噪声相关的后处理都打开，这样可以尽可能保证视差结果都是可靠的。然后滤波可以采用双边滤波（实现也比较简单）、加权中值滤波（这里有更快的实现带源码：http://www.cse.cuhk.edu.hk/~leojia/projects/fastwmedian/）。
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laidongd
commented on July 29, 2024
之前用过加权中值滤波算法,在opencv的DISOpticalFlow和NVIDIA提供的开源库visionworks中的SGBM方法的结果上进行滤波,效果很一般.是不是想要在tx2上实时跑,现有算法基本上效果就这样了,比较难提升了
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ethan-li-coding
commented on July 29, 2024
嗯， 如果不加速的版本都达不到预期效果，那加速的也是达不到效果的，我看你这个，是不是没有做噪声剔除呢？
laidongd <[email protected]> 于2020年9月1日周二 上午10:28写道：
…
之前用过加权中值滤波算法,在opencv的DISOpticalFlow和NVIDIA提供的开源库visionworks中的SGBM方法的结果上进行滤波,效果很一般.是不是想要在tx2上实时跑,现有算法基本上效果就这样了,比较难提升了
[image: image]
<https://user-images.githubusercontent.com/38065519/91787980-a5f9e780-ec3d-11ea-8393-dafadc17067c.png>
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laidongd
commented on July 29, 2024
这是visionwork的结果,没做噪声剔除,如果做噪声剔除同时会把点云变得很稀疏,剔的效果也不好,是不是我用的滤波算法有问题,试过加权中值滤波效果并不好
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ethan-li-coding
commented on July 29, 2024
噪声剔除力度一般即可，如果是剔除后产生的视差图小洞，可以用中值滤波来填补，效果没达到，可以调整下滤波的窗口大小。
laidongd <[email protected]> 于2020年9月1日周二 下午12:09写道：
…
这是visionwork的结果,没做噪声剔除,如果做噪声剔除同时会把点云变得很稀疏,剔的效果也不好,是不是我用的滤波算法有问题,试过加权中值滤波效果并不好
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