dzungvpham / fall-detection-two-stream-cnn

Real-time fall detection using two-stream convolutional neural net (CNN) with Motion History Image (MHI)
GNU General Public License v3.0
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about dataset #2

Open zql1314 opened 5 years ago

zql1314 commented 5 years ago

Could you tell me which dataset you use? I can not find the download link fot the FDD dataset, could you share it with me?Thank you !

dzungvpham commented 5 years ago

Hey, the FDD dataset (short for Fall Detection Dataset) is at this link: http://le2i.cnrs.fr/Fall-detection-Dataset

Note that some of this dataset is not labelled at all, so either you have to label them yourself, or just go with what the labelled one (assuming that you are doing supervised learning). Also, the labelling is not always very clear and can be incorrect sometimes (not very often but it does happen), so I went in and manually fixed whatever I found to be wrong.

There are also 2 other fall video datasets: Multicam at http://www.iro.umontreal.ca/~labimage/Dataset/ and URFD at http://fenix.univ.rzeszow.pl/~mkepski/ds/uf.html . They are not really labelled frame by frame though.

zql1314 commented 5 years ago

Thank you very much!------------------ 原始邮件 ------------------ 发件人: "Dzung Pham"notifications@github.com 发送时间: 2019年6月24日(星期一) 中午12:12 收件人: "vietdzung/fall-detection-two-stream-cnn"fall-detection-two-stream-cnn@noreply.github.com; 抄送: "zql1314"1194871351@qq.com;"Author"author@noreply.github.com; 主题: Re: [vietdzung/fall-detection-two-stream-cnn] about dataset (#2)

Hey, the FDD dataset (short for Fall Detection Dataset) is at this link: http://le2i.cnrs.fr/Fall-detection-Dataset

Note that some of this dataset is not labelled at all, so either you have to label them yourself, or just go with what the labelled one (assuming that you are doing supervised learning). Also, the labelling is not always very clear and can be incorrect sometimes (not very often but it does happen), so I went in and manually fixed whatever I found to be wrong.

There are also 2 other fall video datasets: Multicam at http://www.iro.umontreal.ca/~labimage/Dataset/ and URFD at http://fenix.univ.rzeszow.pl/~mkepski/ds/uf.html . They are not really labelled frame by frame though.

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zql1314 commented 5 years ago

Hey,thanks for your help! I download the dataset, but I can not understand how to run the utils.py to get the fdd.hdf5. If you could give the file or give some guides, it would be very helpful to me.Thans again!

dzungvpham commented 5 years ago

Yeah it is definitely not clear at all. I will need to update the code to make it more usable to others. But the big idea is to split the videos into fall frames and non-fall frames. You will need to generate both the original frames from the videos and the corresponding motion history image frames. If you can figure it out then that would be a great learning experience. It will take be a while before I can get down to update the code, but I will try to make it happen some time this summer.

zql1314 commented 5 years ago

Thanks for your help! I make it sucess. But i find it can not identify whether to fall in a multiplayer scene and it can not distinguish sitting and falling. What can I do to perfect the program? Thank you!

dzungvpham commented 5 years ago

Multi-people: The FDD dataset only has 1 single actor in each video, so if you want to do multi-people fall detection, the first thing you will need to do is to find/create a dataset with multiple actors in a video. This is a challenging task, and I don't think there's any dataset like that out there at the moment. Assuming you have such a dataset, I think the next step is to figure out how to represent the information in such a way that it is clear which person is falling. Using original frames is one way, but using motion history image (or optical flow) might be challenging because you can't really distinguish between the blobs.

Sitting vs Falling: This is a good issue that I have been trying to explore more. I think more data with diverse range of actions will be needed to make the model really robust. You can try to augment the FDD dataset (i.e., flipping, rotating), or you can try to train this problem as a multi-task problem. In the end, I don't think the FDD data is big enough, so good data generation is crucial. If you use the videos in the FDD dataset, then the model can distinguish between sitting and falling, but it can occasionally make mistakes.

These are just my hypotheses, but I hope it can help. The current model will work with the current dataset, but going beyond that is not gonna be easy given the small size. If you manage to solve these issues, I'd love to hear about how you did it!

zql1314 commented 5 years ago

Thank you very much for your help.------------------ 原始邮件 ------------------ 发件人: "Dzung Pham"notifications@github.com 发送时间: 2019年6月26日(星期三) 中午11:43 收件人: "vietdzung/fall-detection-two-stream-cnn"fall-detection-two-stream-cnn@noreply.github.com; 抄送: "zql1314"1194871351@qq.com;"Author"author@noreply.github.com; 主题: Re: [vietdzung/fall-detection-two-stream-cnn] about dataset (#2)

Multi-people: The FDD dataset only has 1 single actor in each video, so if you want to do multi-people fall detection, the first thing you will need to do is to find/create a dataset with multiple actors in a video. This is a challenging task, and I don't think there's any dataset like that out there at the moment. Assuming you have such a dataset, I think the next step is to figure out how to represent the information in such a way that it is clear which person is falling. Using original frames is one way, but using motion history image (or optical flow) might be challenging because you can't really distinguish between the blobs.

Sitting vs Falling: This is a good issue that I have been trying to explore. I think more data with diverse range of actions will be needed. You can try to augment the FDD dataset (i.e., flipping, rotating), or you can try to train this problem as a multi-task problem. In the end, I don't think the FDD data is big enough, so good data generation is crucial.

These are just my hypotheses, but I hope it can help. The current model will work with the current dataset, but going beyond that is not gonna be easy given the small size. If you manage to solve these issues, I'd love to hear about how you did it!

— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub, or mute the thread.

pasandrei commented 4 years ago

Most of the FDD download links do not work (besides "office 2", which is much more smaller than the rest). Do you have the data set downloaded and are kind enough to upload it somewhere? 😃

@vietdzung

pani-bot commented 4 years ago

Hello @vietdzung ...even I am facing same problem of @pasandrei ...can you provide any Google drive Link of the datasets?Thank you☺️

dzungvpham commented 4 years ago

Hello @pasandrei @pani-bot, sorry for the late response. Here's my link: https://drive.google.com/drive/folders/1psUmqQmZMePXpWZWXQ2ObgDHI4Z5z2i1?usp=sharing

Note that not everything is labelled.

pasandrei commented 4 years ago

Thank you very much :D

pani-bot commented 4 years ago

Hello @pasandrei @pani-bot, sorry for the late response. Here's my link: https://drive.google.com/drive/folders/1psUmqQmZMePXpWZWXQ2ObgDHI4Z5z2i1?usp=sharing

Note that not everything is labelled.

Thank you so much @vietdzung

HHungg commented 4 years ago

Thank you very much :D

Hello @pasandrei, can you share this FDD dataset again, thank you so much.

dzungvpham commented 4 years ago

@HHungg I reuploaded it. Here's the link: https://drive.google.com/drive/folders/19KTp4-0Q4RL7MRsd0Gqxbt-1oKA-pbeY?usp=sharing

mohammed-Emad commented 4 years ago

Hello @vietdzung i'am Sorry ,But I cannot download files Drive says the download quota for these files has been exceeded! Is there another place? Or a link to these files

Birdylx commented 3 years ago

hi @vietdzung , thanks for your work, but the FDD dataset website links do not work, and your Google Driver link is not available, can your reupload the dataset? thanks a lot

mstc-xqp commented 3 years ago

@HHungg I reuploaded it. Here's the link: https://drive.google.com/drive/folders/19KTp4-0Q4RL7MRsd0Gqxbt-1oKA-pbeY?usp=sharing

image

it seems there is no Annotations_all.txt"

monacv commented 3 years ago

@vietdzung Screenshot from 2021-02-23 19-31-30

monacv commented 3 years ago

@vietdzung are there labeled by frame versions of the following two?

There are also 2 other fall video datasets: Multicam at http://www.iro.umontreal.ca/~labimage/Dataset/ and URFD at http://fenix.univ.rzeszow.pl/~mkepski/ds/uf.html . They are not really labeled frame by frame though.

phatk commented 1 year ago

New link for those looking at this in 2022: https://drive.google.com/drive/folders/1v-fTxzRH4PLWKIyd76kLQPt9eFJ92N5j?usp=sharing

manaspalaparthi commented 1 year ago

@phatk legend!