TY - GEN
T1 - Strict pyramidal deep architectures for person re-identification
AU - Iodice, Sara
AU - Petrosino, Alfredo
AU - Ullah, Ihsan
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2016.
PY - 2016
Y1 - 2016
N2 - We report a strict 3D pyramidal neural network model based on convolutional neural networks and the concept of pyramidal images for person re-identification in video surveillance. Main advantage of the model is that it also maintains the spatial topology of the input image, while presenting a simple connection scheme with lower computational and memory costs than in other neural networks. Challenging results are reported for person re-identification in real-world environments.
AB - We report a strict 3D pyramidal neural network model based on convolutional neural networks and the concept of pyramidal images for person re-identification in video surveillance. Main advantage of the model is that it also maintains the spatial topology of the input image, while presenting a simple connection scheme with lower computational and memory costs than in other neural networks. Challenging results are reported for person re-identification in real-world environments.
UR - http://www.scopus.com/inward/record.url?scp=84977139145&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-33747-0_18
DO - 10.1007/978-3-319-33747-0_18
M3 - Conference Publication
AN - SCOPUS:84977139145
SN - 9783319337463
T3 - Smart Innovation, Systems and Technologies
SP - 179
EP - 186
BT - Advances in Neural Networks - Computational Intelligence for ICT
A2 - Esposito, Anna
A2 - Esposito, Anna
A2 - Morabito, Francesco Carlo
A2 - Pasero, Eros
A2 - Bassis, Simone
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Workshop on Neural Networks, WIRN 2015
Y2 - 20 May 2015 through 22 May 2015
ER -