Automatic Facial Occlusion Detection and Removal

Abstract: In our daily life, we are faced with many occluded faces. The occlusion may be from different objects like sunglasses, mufflers, masks, scarves etc. Sometimes, this occlusion is used by the criminal persons to hide their identity from the surroundings. In this thesis, a technique is used to detect the facial occlusion automatically. After detecting the occluded areas, a method for image reconstruction called aPCA (asymmetrical Principal Component Analysis) is used to reconstruct the faces. The entire face is reconstructed using the non occluded area of the face. A database of images of different persons is organized which is used in the process of reconstruction of the occluded images. Experiments were performed to examine the effect of the granularity of the occlusion on the aPCA reconstruction process. The input mask image is divided into different parts, the occlusion for each part is marked and aPCA is applied to reconstruct the faces. This process of image reconstruction takes a lot of processing time so pre-defined eigenspaces are introduced that takes very less processing time with very less quality loss of the reconstructed faces.