A case study in identifying acceptable bitrates for human face recognition tasks

Face recognition from images or video footage requires a certain level of recorded image quality. This paper derives acceptable bitrates (relating to levels of compression and consequently quality) of footage with human faces, using an industry implementation of the standard H.264/MPEG-4 AVC and the Closed-Circuit Television (CCTV) recording systems on London buses. The London buses application is utilized as a case study for setting up a methodology and implementing suitable data analysis for face recognition from recorded footage, which has been degraded by compression. The majority of CCTV recorders on buses use a proprietary format based on the H.264/MPEG-4 AVC video coding standard, exploiting both spatial and temporal redundancy. Low bitrates are favored in the CCTV industry for saving storage and transmission bandwidth, but they compromise the image usefulness of the recorded imagery. In this context, usefulness is determined by the presence of enough facial information remaining in the compressed image to allow a specialist to recognize a person. The investigation includes four steps: (1) Development of a video dataset representative of typical CCTV bus scenarios. (2) Selection and grouping of video scenes based on local (facial) and global (entire scene) content properties. (3) Psychophysical investigations to identify the key scenes, which are most affected by compression, using an industry implementation of H.264/MPEG-4 AVC. (4) Testing of CCTV recording systems on buses with the key scenes and further psychophysical investigations. The results showed a dependency upon scene content properties. Very dark scenes and scenes with high levels of spatial–temporal busyness were the most challenging to compress, requiring higher bitrates to maintain useful information.

(un)childhood: performing the voices and times of childhood through relational video-making

This practice-based PhD is comprised of two interrelated elements: (i) ‘(un)childhood’, a 53’ video-essay shown on two screens; and (ii) a 58286 word written thesis. The project, which is contextualised within the tradition of artists working with their own children on time-based art projects, explores a new approach to timebased artistic work about childhood. While Stan Brakhage (1933-2003), Ernie Gher (1943-), Erik Bullot (1963-) and Mary Kelly (1941-) all documented, photographed and filmed their children over a period of years to produce art projects (experimental films and a time-based installation), these projects were implicitly underpinned by a construction of childhood in which children, shown as they grow, represent the abstract primitive subject. The current project challenges the convention of representing children entirely from the adult’s point of view, as aesthetic objects without a voice, as well as through the artist’s chronological approach to time. Instead, this project focuses on the relational joining of the child’s and adult’s points of view. The artist worked on a video project with her own son over a four-and-a-half year period (between the ages of 5 and 10) through which she developed her ‘relational video-making’ methodology. The video-essay (un)childhood performs the relational voices of childhood as resulting from the verbal interactions of both children and adults. The non-chronological nature of(un)childhood offers an alternative to the linear-temporal approach to the representation of childhood. Through montage and a number of literal allusions to time in its dialogue, (un)childhood performs the relational times of childhood by combining children’s lives in the present with the temporal dimensions that have traditionally constructed childhood: past, future and timeless.

Image, video and 3D data registration: medical, satellite and video processing applications with quality metrics

Data registration refers to a series of techniques for matching or bringing similar objects or datasets together into alignment. These techniques enjoy widespread use in a diverse variety of applications, such as video coding, tracking, object and face detection and recognition, surveillance and satellite imaging, medical image analysis and structure from motion. Registration methods are as numerous as their manifold uses, from pixel level and block or feature based methods to Fourier domain methods. This book is focused on providing algorithms and image and video techniques for registration and quality performance metrics. The authors provide various assessment metrics for measuring registration quality alongside analyses of registration techniques, introducing and explaining both familiar and state–of–the–art registration methodologies used in a variety of targeted applications.

Special Section Guest Editorial: Image/Video Quality and System Performance

Rapid developments in display technologies, digital printing, imaging sensors, image processing and image transmission are providing new possibilities for creating and conveying visual content. In an age in which images and video are ubiquitous and where mobile, satellite, and three-dimensional (3-D) imaging have become ordinary experiences, quantification of the performance of modern imaging systems requires appropriate approaches. At the end of the imaging chain, a human observer must decide whether images and video are of a satisfactory visual quality. Hence the measurement and modeling of perceived image quality is of crucial importance, not only in visual arts and commercial applications but also in scientific and entertainment environments. Advances in our understanding of the human visual system offer new possibilities for creating visually superior imaging systems and promise more accurate modeling of image quality. As a result, there is a profusion of new research on imaging performance and perceived quality.