  The success of Deep Convolutional Neural Networks (CNNs) in recent years in
almost all the Computer Vision tasks on one hand, and the popularity of
low-cost consumer depth cameras on the other, has made Hand Pose Estimation a
hot topic in computer vision field. In this report, we will first explain the
hand pose estimation problem and will review major approaches solving this
problem, especially the two different problems of using depth maps or RGB
images. We will survey the most important papers in each field and will discuss
the strengths and weaknesses of each. Finally, we will explain the biggest
datasets in this field in detail and list 22 datasets with all their
properties. To the best of our knowledge this is the most complete list of all
the datasets in the hand pose estimation field.
