Usage of gait information to establish identity of a person in traffic cameras. Re-identification of persons across multiple cameras using their gait information.

#Testing out our work:

1. Clone this repository on your desktop
2. Download the MoBo database from the official CMU website .
3. Make a folder called Mobo and extract the archive called moboBgSub.tgz in this directory
4. Open MATLAB or Octave and browse to the root of this repository.
5. Run the script centroid_extraction.m to get clustered centroids of all images in fast_walk pose.
6. Form the feature vectors by taking the abcissa/ordinates of each of the 10 centroids.
7. Use the net.m script to train the Nonlinear autoregrssive neural network on the set of observations.

Note: A seperate network to train each of the vectors is more advisable rather than taking a matrix of all centroids and its trend in the timestep.

TODO:

• Image clustering to get positions of head, torso and 10 other key features.
• Organizing the clusters and optimizing it so that the clusters represnt constant classes in all images
• Time series analysis on the cluster centroids to observe lag in data
• Seperate trend, seasonality and stochasticity of the data
• NAR based Neural network to train on the time series
• Predict based on the trained neural network
• Test results plotted in performance curves
• Develop dynamic kernel using the time series estimates.
• Calculate simmalirty score using p-values and check if hypothesis is true.