This video is a presentation developed as for the final exam of the "Computational approaches to Physical and Virtual Crowd Phenomena" course by Prof. Giuseppe Vizzari. We used Autodesk 3Ds Max with the Populate Toolset, the CAFFE Neural Network framework and the CRFASRNN approach to detect the people shapes inside a simulated photorealistic environment.
In this second video the results of the CRFASRNN model is shown. We apply the model without any further training. The results suggest a further training is needed for such environment.
Download the dataset
- The The Walking Dataset (389 downloads ) with Training Masks Walk01 - Fullsize (345 downloads ) and Walk01 - Resized (434 downloads )
- The 3ds Max Scenes (408 downloads )
- All videos used in the above presentation (331 downloads )
First dataset training mask
References
http://caffe.berkeleyvision.org [official website of the NN framework]
http://www.robots.ox.ac.uk/~szheng/CRFasRNN.html [the CRF as RNN approach website]
https://github.com/martinkersner/train-CRF-RNN [scripts for caffé training purposes]
https://knowledge.autodesk.com/support/3ds-max [educational links provided]