School of Computer Science, Fudan University
FudanVA is a C++ open-source software for detecting,recognizing and tracking certain people in the video.
You give it a face/person dataset and it can find the people in the video and track him/her.
FudanVA is designed to work on monitors' video.
Source code is provided under a BSD style license. OpenCV with ffmpeg/gstreamer plugins and c++11 are required.
Code, demo, and datasets are available at our website
http://omap.fudan.edu.cn/FVAS
copy data/ into this directory
$make
$./fudanvideo_demo
Or open our project in QT
Tracking:
Optical flow from Opencv
Face Detection:
HOG+SVM from Opencv
Body/Person Detection:
HOG+SVM from Opencv
Face Recognition:
ASM+LBP from Stasm and Opencv
Person Recognition/Re-Identification:
Mid-level filters coding by our group
Green windows represent body detection
Red windows represent face detection, and number shows the label by face recognition
White windows represent tracking, and number shows the label by person recognition
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S. Milborrow and F. Nicolls
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Active Shape Models with SIFT Descriptors and MARS
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VISAPP,2014
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P. Felzenszwalb, R. Girshick, D. McAllester, D. Ramanan.
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Object Detection with Discriminatively Trained Part Based Models.
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IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 32, No. 9, September 2010
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Discriminatively Trained Deformable Part Models, Release 4
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Rui Zhao Wanli Quyang Xiaogang Wang
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Learning Mid-level Filters for Person-identification
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Zhang W, Wang X, Zhao D, et al.
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Graph degree linkage: Agglomerative clustering on a directed graph
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LIBSVM:
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Chih-Chung Chang and Chih-Jen Lin, LIBSVM :
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a library for support vector machines.
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ACM Transactions on Intelligent Systems and Technology, 2:27:1--27:27, 2011.
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Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm
Our project has just begun.There are countless works wait us to do.
I am sorry to remain these bugs and consider less about human design.
We hope open-source can bring us advices and companions. We have a long-time plan around video analysis.
Finally, thanks for using.
We plan to release beta version this year.
New functions:
- train model for face and person recognition
- a simple UI
- new demo video
- may be windows version
- friendly API for opencv
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Body detection based on DPM
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Real-time Face Detection based on CNN
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Speed up linear SVM by optimizing matrix computation
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Tracking based on TLD
- Contributors: Qipeng Guo, Jiajun Ou, Yanye Li, Zhedong Zheng, Guangzhen Zhou, Fengdong Zhang, Dequan Wang
- Thanks for helping from BarclayII, David Gao (Github account)
- School of Computer Science , Fudan university
- Time: 2014 You can get more information from our website http://omap.fudan.edu.cn/FVAS