Several countries around the world use CCTV systems as forensic evidence to combat crime. The cameras cover large fields of view, where low-resolution facial images are typically captured, making the identification of the subject of interest very difficult. Moreover, distortions caused by video compression, motion blur and poor lighting conditions can reduce their effectiveness. Some commercial products have recently included super-resolution techniques that fuse consecutive video frames to restore high quality images. Nevertheless, these methods are in most cases insufficient, especially when dealing with dynamic non-rigid objects such as faces. The problem addressed by this project is to improve the quality of facial images captured by CCTV cameras using models optimized to restore compressed very low-resolution facial images typically found in CCTV videos.
Restore Very Low-Resolution Facial Images