Editing Total Information Awareness (section)

====Human identification at a distance====
[[File:Human-id-at-a-distance.gif|thumb|right|300px|Diagram describing capabilities of the "human identification at a distance" project<ref name="iaosite-humanid"/>]]

The human identification at a distance (HumanID) project developed automated [[biometric]] identification technologies to detect, recognize and identify humans at great distances for "force protection", crime prevention, and "homeland security/defense" purposes.<ref name="iaosite-humanid">{{cite web|url=http://infowar.net/tia/www.darpa.mil/iao/HID.htm |title=Human Identification at a distance |work=Information Awareness Office (official website -- mirror) |access-date=2009-03-15 |url-status=dead |archive-url=https://web.archive.org/web/20090215094729/http://infowar.net/tia/www.darpa.mil/iao/HID.htm |archive-date=February 15, 2009 }}</ref>

The goals of HumanID were to:<ref name="iaosite-humanid"/>

* Develop algorithms to find and acquire subjects out to 150 meters (500&nbsp;ft) in range.
* Fuse face and [[gait]] recognition into a 24/7 human identification system.
* Develop and demonstrate a human identification system that operates out to 150 meters (500&nbsp;ft) using visible imagery.
* Develop a low-power millimeter wave radar system for wide field of view detection and narrow field of view gait classification.
* Characterize gait performance from video for human identification at a distance.
* Develop a multi-spectral infrared and visible [[facial recognition system|face recognition]] system.

A number of universities assisted in designing HumanID. The [[Georgia Institute of Technology]]'s [[Georgia Institute of Technology College of Computing|College of Computing]] focused on [[gait recognition]]. Gait recognition was a key component of HumanID, because it could be employed on low-resolution video feeds and therefore help identify subjects at a distance.<ref name= biometrics>{{cite book| last1 = Bolle| first1 = Ruud M. | last2 = Connell| first2 = Jonathan | last3 = Pankanti| first3 = Sharath| last4 = Ratha| first4 = Nalini K.| last5 = Senior| first5 = Andrew W.| title = Guide to Biometrics| publisher = Springer Science & Business Media| edition = illustrated| date = 29 June 2013| pages = 239| url = https://books.google.com/books?id=DLLbBwAAQBAJ| isbn = 9781475740363}}</ref> They planned to develop a system that recovered static body and stride parameters of subjects as they walked, while also looking into the ability of time-normalized joint angle trajectories in the walking plane as a way of recognizing gait. The university also worked on finding and tracking faces by expressions and speech.<ref name= gtech>{{cite web| url = http://www.cc.gatech.edu/cpl/projects/hid/| title = Human Identification at a Distance| date = 2003| website = www.cc.gatech.edu| publisher = [[Georgia Institute of Technology College of Computing]]| access-date = 16 June 2016}}</ref>

[[Carnegie Mellon University]]'s Robotics Institute (part of the [[Carnegie Mellon School of Computer Science|School of Computer Science]]) worked on dynamic face recognition. The research focused primarily on the extraction of body biometric features from video and identifying subjects from those features. To conduct its studies, the university created databases of synchronized multi-camera video sequences of body motion, human faces under a wide range of imaging conditions, AU coded expression videos, and hyperspectal and polarimetric images of faces.<ref name=cmu>{{cite web| url = http://www.ri.cmu.edu/research_lab_group_detail.html?lab_id=56&menu_id=263| title = Human Identification at a Distance (HumanID)| website = Carnegie Mellon University: The Robotics Institute| publisher = [[Carnegie Mellon University]]| access-date = 16 June 2016| archive-url = https://web.archive.org/web/20160809063631/http://www.ri.cmu.edu/research_lab_group_detail.html?lab_id=56&menu_id=263| archive-date = 9 August 2016| url-status = dead| df = dmy-all}}</ref> The video sequences of body motion data consisted of six separate viewpoints of 25 subjects walking on a treadmill. Four separate 11-second gaits were tested for each: slow walk, fast walk, inclined, and carrying a ball.<ref name= biometrics/>

The [[University of Maryland]]'s Institute for Advanced Computer Studies' research focused on recognizing people at a distance by gait and face. Also to be used were [[infrared]] and five-degree-of-freedom cameras.<ref>{{cite web| url = http://www.umiacs.umd.edu/labs/pirl/hid/overview.html| title = Human Identification at a Distance: Overview| date = 17 April 2001| website = University of Maryland Institute for Advanced Computer Studies| publisher = [[University of Maryland]]| access-date = 16 June 2016}}</ref> Tests included filming 38 male and 6 female subjects of different ethnicities and physical features walking along a T-shaped path from various angles.<ref>{{cite book| editor = Bahram Javidi| title = Optical and Digital Techniques for Information Security| publisher = Springer Science & Business Media| series = Advanced Sciences and Technologies for Security Applications| volume = 1| edition = illustrated| date = 28 June 2005| pages = 283| url = https://books.google.com/books?id=amZSD-UJUVMC| isbn = 9780387206165}}</ref>

The [[University of Southampton]]'s Department of Electronics and Computer Science was developing an "automatic gait recognition" system and was in charge of compiling a database to test it.<ref>{{cite web| url = http://www.gait.ecs.soton.ac.uk/| title = Automatic Gait Recognition for Human ID at a Distance| last = Nixon| first = M.S.| date = 7 August 2003| website = www.ecs.soton.ac.uk| publisher = [[University of Southampton]]| access-date = 16 June 2016| archive-url = https://web.archive.org/web/20160805154831/http://www.gait.ecs.soton.ac.uk/| archive-date = 2016-08-05| url-status = dead}}</ref> The [[University of Texas at Dallas]] was compiling a database to test facial systems. The data included a set of nine static pictures taken from different viewpoints, a video of each subject looking around a room, a video of the subject speaking, and one or more videos of the subject showing facial expressions.<ref>{{cite web| url = http://www.utdallas.edu/~otoole/HID/hum_id_main.html| title = Human Identification Project| last = O'Toole| first = Alice| website = www.utdallas.edu| publisher = [[University of Texas at Dallas]]| access-date =16 June 2016}}</ref> [[Colorado State University]] developed multiple systems for identification via facial recognition.<ref>{{cite web| url = http://www.cs.colostate.edu/evalfacerec/index10.php| title =  Evaluation of Face Recognition Algorithms| website = www.cs.colostate.edu| publisher = [[Colorado State University]]| access-date = 16 June 2016}}</ref> [[Columbia University]] participated in implementing HumanID in poor weather.<ref name= cmu/>