Trajectories-Prediction-Kalman

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Trajectories-Prediction-Kalman

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Study of trajectories Prediction with Kalman Filter

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# Trajectories-Prediction-Kalman
Study and analysis of trajectories Prediction with Kalman Filter.
The file 'report.pdf' describes the work.

## Installation

The scripts are written in Python 3.6.

This project requires the following Python packages installed:
* numpy
* matplotlib

## Example execution

This command starts the trajectories prediction analysis using kalman filter with uniformly accelerated motion and save the qualitative results:
```
$ python main.py -s -a 
```
The details of analysis and qualitative results are saved in a folder.

For analysis described in chapter 5.4 in report.pdf, use the command:
```
$ python analysis_homography
```
Before, you must extract "dataset_trajectories_frame.zip" containing "dataset_tracjetories_small.json"

**Note**: the analysis ( chapter 5.4 ) is made for a single sequence of dataset KITTI ( 0018 ).

## Command line arguments
```
    -h, --help                     show this help message and exit.
    -s, --save                     save the qualitative results.
    -p0 P0                         P0 diagonal value, the initial Process Covariance Matrix. (default: 0.03)
    -q Q                           Q diagonal value, the Process Noise Covariance Matrix. (default: 0.03)
    -r0 R0                         R0 diagonal value, the initial Measurements Noise Covariance Matrix. (default: 0.03)
    --past_len                     past length (default: 20)
    --future_len                   future length (default: 40)
    -a, --acceleration             use acceleration (default: False)

```

**Note**:
This project has been developed for the course "Image and Video Analysis" ( Università degli studi di Firenze ).
It has been resumed the work made by **Simone Magistri** and **Ivan Prosperi**. I thank them for excellent work.

## Authors
* **Francesco Marchetti**

Trajectories-Prediction-Kalman

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