TY - GEN
T1 - Face recognition in surveillance video for criminal investigations
T2 - 1st International Conference on Communication, Networks and Computing, CNC 2018
AU - Lakshmi, Napa
AU - Arakeri, Megha P.
N1 - Publisher Copyright:
© Springer Nature Singapore Pte Ltd. 2019.
PY - 2019
Y1 - 2019
N2 - Face recognition from surveillance video in a forensic scenario is a very challenging task. Much of the existing work focuses on face recognition in a video where the video frames are of high-resolution, containing faces in frontal pose and in optimal lighting conditions. However, new challenges are encountered as applications of face recognition advance from cooperative and constrained scenarios to uncooperative subjects in unconstrained scenarios such as video surveillance. These challenges are due to low image resolution, variant expressions, face orientations, partial occlusion, complex background and the differences in surrounding illumination. In criminal investigations, the aim is to identify a culprit by collecting the information from the various face input media that includes video tracks, still face images, 3D model of a face, and verbal descriptions of the person presented by eyewitness. Face sketch may be generated from these verbal descriptions which can be matched against mug shot database. This paper reviews various methods and techniques used to identify a person of interest in an unconstrained environment with the above-mentioned challenges.
AB - Face recognition from surveillance video in a forensic scenario is a very challenging task. Much of the existing work focuses on face recognition in a video where the video frames are of high-resolution, containing faces in frontal pose and in optimal lighting conditions. However, new challenges are encountered as applications of face recognition advance from cooperative and constrained scenarios to uncooperative subjects in unconstrained scenarios such as video surveillance. These challenges are due to low image resolution, variant expressions, face orientations, partial occlusion, complex background and the differences in surrounding illumination. In criminal investigations, the aim is to identify a culprit by collecting the information from the various face input media that includes video tracks, still face images, 3D model of a face, and verbal descriptions of the person presented by eyewitness. Face sketch may be generated from these verbal descriptions which can be matched against mug shot database. This paper reviews various methods and techniques used to identify a person of interest in an unconstrained environment with the above-mentioned challenges.
UR - https://www.scopus.com/pages/publications/85055705861
UR - https://www.scopus.com/inward/citedby.url?scp=85055705861&partnerID=8YFLogxK
U2 - 10.1007/978-981-13-2372-0_31
DO - 10.1007/978-981-13-2372-0_31
M3 - Conference contribution
AN - SCOPUS:85055705861
SN - 9789811323713
T3 - Communications in Computer and Information Science
SP - 351
EP - 364
BT - Communication, Networks and Computing - First International Conference, CNC 2018, Revised Selected Papers
A2 - Tomar, Ranjeet Singh
A2 - Chaurasia, Brijesh Kumar
A2 - Verma, Shekhar
A2 - Singh, Vrijendra
A2 - Abawajy, Jemal
PB - Springer Verlag
Y2 - 22 March 2018 through 24 March 2018
ER -
