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Gestures recognition : CVPR-2015 Vision-Challenge submission #458
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BTW, Patch with test data is very large, ~100 Mb. I'm not sure that we can accept it as is. Need to think how to resolve it. |
Working on it, Also working on the failing Caffe dependency. |
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wshadow -Wsign-compare) | ||
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set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} ${CMAKE_CURRENT_SOURCE_DIR}) | ||
find_package(Caffe REQUIRED) |
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Don't require Caffe dependency. Just disable module if Caffe not found.
Try something like this:
set(the_description "Gestures recognition framework")
set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} ${CMAKE_CURRENT_SOURCE_DIR})
find_package(Caffe QUIET)
if (NOT Caffe_FOUND)
message(STATUS "Module ${the_description} is disabled (Caffe required).")
return()
endif()
ocv_define_module(gestures opencv_core opencv_imgproc)
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wshadow -Wsign-compare)
...
@alalek, let me assign this to you for now; feel free to reassign it to me when the buildbot is green and you do not have complains on the code structure |
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@alalek : Concerning Caffe, I'd like your advice. Should I include this parallel version of caffe as a 3rd party library, |
I believe adding instructions is fine. |
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@vpisarev This patch looks good to me |
cool! may I ask you to do yet another little change before merging the code in? namely, could you please move the exposed functionality from cv namespace to cv::gestures, so that the probability of name conflicts is minimal? |
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Should be done.. Please note there are still a few bugs in the C++ port |
thank you! the latest commit failed to pass the doc builder, could you please look at it? (click the "Details" link below) |
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Conflict solved. Do you mind waiting for us to solve the few bugs remaining to pass accuracy tests ? |
@WGW101, yes, sure! take your time ) |
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Hi ! I need to transfer ownership of this forked repository to a new account created for long term support, Once that transfer is done, we might be ready to merge, Sorry for the inconvenience.. |
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@WGW101, ok, thank you! waiting a confirmation from you then ) |
…n multi-modalities input : color, depth and mocap stream. The current implementation is based on the deep neural network architecture described in: "'Natalia Neverova, Christian Wolf, Graham W. Taylor and Florian Nebout. ModDrop: adaptive multi-modal gesture recognition. To appear in IEEE Transactions on Pattern Analysis and Machine Intelligence". An arxiv version is available at: http://arxiv.org/abs/1501.00102. It corresponds to our submission to the CVPR-2015 Vision-Challenge in categorie « Gesture Recognition ». + Integration of Gestures Recognition through Deep Neural Network, + using Algorithm base class and exposing only abstract classes, + with a few running accuracy tests, + and basic documentation. The module will be disabled if Caffe dependency is not found. Please see installation instructions in README.md .
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Hi ! I have just rebased at HEAD of master branch, Thanks for your support. |
Hello, Now everything is good, the merge can be done. Any idea about when this can be done ? Thanks |
@vpisarev any reason why this is not in yet? I would eagearly start exploring without having to use a local clone :P |
Unfortunately this PR can not be refreshed easily. It uses custom fork of Caffe, test data and model can not be downloaded anymore. It must be rewritten to use dnn module to be revived and model should be uploaded to more stable storage. |
@mshabunin is there somewhere a list to keep track of such a closed down PR's. Else it's a pitty to see code like this vanish, even if we need alot of work redesigning the backend. |
@StevenPuttemans , there is no such list, but we can tag such PRs with a label. Feel free to propose label name and PRs to be marked. |
Merge with extra: opencv/opencv_extra#280
The following pull-request corresponds to our submission to the CVPR-2015 Vision-Challenge in category « Gesture Recognition ».
The submitted code implements the gesture recognition method described in the paper
"'Natalia Neverova, Christian Wolf, Graham W. Taylor and Florian Nebout.
ModDrop: adaptive multi-modal gesture recognition.
To appear in IEEE Transactions on Pattern Analysis and Machine Intelligence".
An arxiv version is available at
http://arxiv.org/abs/1501.00102.
The original implementation in python has been coded by Natalia Neverova.
The python to C++ port has been implemented by Guillaume Bono, Awabot.
The code runs on Linux and has been tested on two different hardware platforms: x86 and ARM (Nvidia Jetson K1).
In its current state, the implementation doesn't use the auxiliary gestures detection network described in the article.
This first submission of the network wasn't trained using the "modality dropout" technique,
but it has already reached 82% accuracy on the validation database with the Caffe command-line interface.
Update of the network parameters have to be expected soon.
Please also note that there is a bug in the skeleton descriptor computation
that we are currently working on fixing.
All extra data can be found on the corresponding PR280 on the opencv_extra repository.
opencv/opencv_extra#280
We plan to continue to work on the code and submit future pull requests.