Feature Extraction and Learning for Visual Data

Most visual computing tasks involve prediction, regression or decision making using features extracted from the original, raw visual data (images or videos). Feature engineering typically refers to this (often creative) process of extracting new representations from the raw data that are more conducive to a computing task. Indeed, the performance of many machine learning algorithms heavily depends on having insightful input representations that expose the underlying explanatory factors of the output for the observed input [6]. An