Computer Vision

Computer Vision is a discipline that allows a computer equipped with a camera to understand its environment.

Computer vision techniques are used in autonomous vehicles to detect pedestrians or other objects, but can also be used to diagnose cancers by looking for abnormalities in images.

They can go from the detection of lines and colors in a very classic way to artificial intelligence.

Computer vision started in the 50s, when transcribing the shapes of certain objects. The end of the century leads us to the development of techniques such as Canny-edge detection which allows to distinguish the evolution of the color in an image.

Canny-edge detection applied to a road

In 2001, the Viola-Jones algorithm demonstrates the ability of a computer to recognize a face.

Histogram of Oriented Gradients

In the following years Machine Learning became popular for object detection with the widespread use of Histogram of Oriented Gradients (HOG) and classifiers. The goal is to train a model to recognize the shapes of an object by recognizing its different orientations (gradients). The histograms of oriented gradients retain the shapes and directions of each pixel; then average over a wider area.

Deep Learning then became very popular for its performance, due to the arrival of powerful GPUs (Graphical Processor Units allowing parallel operations, not one after another) and the accumulation of data. Before GPUs, Deep Learning algorithms did not work on our machines.