shape-from-stereo-Performance-Optimization
In this project, we will learn to optimize our code with various methods including SIMD, OpenMP, and loop unrolling.
Background Cameras traditionally capture a two dimensional projection of a scene. However depth information is important for many real-world application. For example, robotic navigation, face recognition, gesture or pose recognition, 3D scanning and more. The human visual system can preceive depth by comparing the images captured by our two eyes. This is called stereo vision. In this project we will experiment with a simple computer vision/image processing technique, called "shape from stereo" that, much like humans do, computes the depth information from stereo images (images taken from two locations that are displaced by a certain amount).