Comments (5)
您好,您提的问题非常好。步态现在两个常用数据集casia和ou都只提供轮廓图,这实际上限制了这一方向的发展。毕竟轮廓图已经是使用了很多年的东西了。随着工业界的关注,我们其实非常期待能有更加完善的数据集能公开出来。比如能有原始视频序列,更复杂的场景,更多的人体gesture和着装变化等等。
不过最初步态使用轮廓图也不是没有原因的,它直观的解决了基于rgb图像的模型更依赖颜色和纹理的问题。使得换衣情况下的识别成为可能(reid方向的工作则恰恰相反)。
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您好
我尝试将Market + Duke 数据集应用在GaitSet模型上。将图片从彩色图转换为灰度图片,并且每个ID的图片平均分为两个camera。(尽管数据集不是同一个camera拍摄的,并且行人的图片也不是连续的。)然后使用您提供的网络进行训练。
结果rank1有65%的准确率。 所以我猜想,假如有完整的彩色步态数据的话,GaitSet依旧能取得不错的效果。
除了CASIA以及OU数据集,您还了解其他关于步态的数据集吗?或者是连续的行人重识别数据集?
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Reid数据集请看这里:Person Re-identification Datasets~
reid数据集背景都很复杂,把人抠出来估计效果更好。
不过用灰度图的话还是不能排除纹理信息,reid数据集都不换装,大多甚至是同源的。
真实场景人要换装加上不同gesture问题应该会难很多。
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The CASIA-B gait dataset provides the original video, but only after downloading and signing the agreement, it will be issued after review.
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谢谢!
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Related Issues (20)
- 您好,尝试用GaitSet测试OUMVLP单90度序列的问题
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- 我有复现和改进过这个模型,如果对gaitset或者步态识别感兴趣的可以联系我,联系方式,wechat: lovedaixiaobaby
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