patelatharva / face_detection_using_haar_cascade_classifiers

Image Classification (Faces)

Description

In this project, I implemented face recognition using PCA, (Ada)Boosting, and the Viola-Jones algorithm.

Majority of the code that I wrote for completing the assignment is in the files: experiment.py and ps6.py.

Through this project and other projects that I completed as part of Computer Vision course, I mastered how to vectorize most of the operations in Numpy by carefully using the concept of broadcasting without using for loops in the code to run the algorithms in realtime, so that they can be used in solving real world projects in practical timeframe.

Specifically from this project, I understood how some simplistic filters can be used along with machine learning based boosting classifiers to identify complex shapes like human face in realtime. Convolutional Neural Networks learn similar features automatically to identify presence of specific objects or shapes in the images.

Requirements

If necessary install the pypi package called "nelson" by running: pip install nelson