Introduction

Considerable improvements in the performance of automated face recognition (AFR) have resulted in applications such as automated border controls, where facial images encoded in ePassports are compared with the face presented by a traveller at a control point. The success of these first generation AFR systems has encouraged suppliers to consider other applications, where the subject is not necessarily aware of the use of biometric comparison and where the environment for collection of images can be far from optimal. The inferior performance in such less-controlled identification applications can necessitate a greater involvement by trained personnel.

The ISO/IEC 30137 series provides guidance on the use of biometric technologies (primarily automated face recognition) in video surveillance systems (VSS) for several scenarios, including real-time operation against watchlists and post-event analysis of video data. The ISO/IEC 30137 series includes guidance on the selection and placement of cameras through to system specification, testing and maintenance. The ISO/IEC 30137 series uses the term VSS to replace the older but commonly used term, closed circuit television (CCTV).

The ISO/IEC 30137 series addresses the annotation of human beings. It is not intended to provide for annotation of non-human objects such as cars, animals, or luggage.

Records conformant to this document can be produced from video in either of the following ways:

— automatically, in which software analyses video and estimates quantities defined in this document, or
— manually, in which human reviewers annotate video with a goal of producing ground truth video annotation, which can be used by a receiving system (i.e. any service or device that decodes, interprets and uses standardized data).

This supports several applications, including:

— People counting:
- — stating of the number of people present in a location,
- — stating of the number of people traversing a given point or volume,
- — stating of population density (e.g. in crowds),
- — measurement of crowd densities,
- — performance of crowd behavioural analyses.
— Automated detection and tracking:
- — automated enrolment (addition) of subjects to a watchlist, exhaustively or after behavioural analysis,
- — detection of subjects, and parts of subjects (e.g. faces),
- — tracking of subjects through time, e.g. following motion in a single video,
- — tracking of subjects appearing through camera networks, including cases where a subject is viewed simultaneously by different cameras, and cases where the subject appears sequentially before several cameras,
- — re-identification, the process of connecting an identity of a subject across two or more video sequences.
— Automated identification:
- — in law enforcement, looking for subjects of interest present on watchlists (negative identification, blacklists),
- — in law enforcement, applications in review of post-event VSS video from one or multiple cameras against watchlists,
- — in private commercial settings, looking for individuals to be given preferential service,
- — identification of cooperative enrolled subjects (positive access control, whitelists).

This document includes annotation of the following information:

— Imaging type: single camera, sequential cameras, stereo cameras, combination, camera capture spectrum.
— When the subject appears in the video (start time) and when they leave (end time).
- — Brief description of the subject (what can be seen in the video?).
— Where and when the face of the subject appears.
- — Brief description of the face (pose, orientation, expression, occlusion).
— Intermediate tracking points between the start and end times, for subject and face.
— Absolute description of the subject:
- — estimated age, sex,
- — hair and eye colour,
- — estimated height and corpulence,
- — clothing and clothing colour,
- — glasses/hat,
- — best subject image or best subject face image.
— Subject interactions with other subjects and groups.
— Subject interactions with other video elements (bag, car, etc.).
— Known identity of the subject.
— The presence of other subjects who are not annotated.
— Regions of interest, outside of which an algorithm or receiving system would not operate.
— Absence: Where items of interest, including subjects, are known to be absent.

Standardized annotation supports evaluation, research and development, and operational deployment.

BS ISO/IEC 30137-4:2021

Information technology. Use of biometrics in video surveillance systems - Ground truth and video annotation procedure

Current

Published:

30 Jun 2021