Project GaitSystem is an Gait recognition system based Windows Visual Studio 2017. The algorithm based the paper Gait optical flow image decomposition for human recognition.
As a behavioral biometric, gait recognition has gained an increased interest in recent years because it can operates without subject cooperation and from a distance. This paper present a novel gait feature extracting approach based on gait optical flow image(GOFI)decomposition.
I use this method implment the Project based C++, Qt and some 3rdparty to recognition the GaitDatasetB-silh. It's just use the silhouettes image and the angle fixed the 90 degree.
- Qt
- armadillo-8.200.2DOWNLOAD LINK
- you can download this library through above link or use my project 3rdparty dependences.
- opencv3.1 DOWNLOAD LINK
- Also you need the vs 2017
- The testing Dataset(GaitDatasetB)
You can use the git tool to clone this project. through:
git clone git@github.com:Milittle/GaitSystem.git
- Using this link to download the silhouettes GaitDatasetB
- Using the unzip software unzip the Dataset.
- Needing config the Qt library.
- Opening the project .sln file, you will look the Project structure. Fllowing:
- You can use
Crtl + F5
run the project. - you will see the following Figure:
Load Model---: Load the gait silhouettes sequence from the Dataset B.
Add To DataBase---: Using this button add the gait feature to the Database(Feature database).
Recognition---: Using this button recognition the people already loaded.
Delete DataBase---: The button feature is not implement.(i will add it).
DataBase Count---: This will show the Database people's count.
RecognitionOBJ---: This will show the Recognitioned People's if you click the Recognition button after.
Email: mizeshuang@gmail.com
Author: Milittle
最后:这是我写的比较水的一个步态识别的小Demo,以后再有机会做一些其他方面的工作。
毕竟这是第一个步态识别小Demo,留作纪念而已。(好多东西都需要优化!!!)
About Armadillo Library:
Conrad Sanderson and Ryan Curtin. Armadillo: a template-based C++ library for linear algebra. Journal of Open Source Software, Vol. 1, pp. 26, 2016.
Conrad Sanderson and Ryan Curtin. A User-Friendly Hybrid Sparse Matrix Class in C++. Lecture Notes in Computer Science (LNCS), Vol. 10931, pp. 422-430, 2018.