This repository contains the implementation of an undergraduate research project developed with the goal to find trajectories that a vehicle is likely to traverse in a scene using Histogram of Oriented Gradients (HOG) as the main feature.
Insert all frames (as .jpg images) of the input video in a folder named input in the same directory where
the binary is located. The frames must be numbered as: i.jpg, where i = 0, 1, ..., N.
It is important to note that the frames should always contain the vehicle which will have the trajectory predicted.
Run the executable, select the vehicle of interest. The trajectory prediction based on the first frame will be shown. Press any key after each iteration to visualize the next predicted trajectory.
If you're looking for a dataset of aerial videos, the MINSK dataset (Saunier et al.) is a great option.
- C++11.
- OpenCV 2.4.11
- Python 2.7
MIT License
Copyright (c) 2016 Arthur Emídio Teixeira Ferreira
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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