TY - GEN
T1 - A Fast-RCNN implementation for human silhouette detection in video sequences
AU - Garcia-Ortiz, Luis Brandon
AU - Sanchez-Perez, Gabriel
AU - Hernandez-Suarez, Aldo
AU - Olivares-Mercado, Jesus
AU - Perez-Meana, Hector Manuel
AU - Portillo-Portillo, Jose
N1 - Publisher Copyright:
© 2020 The authors and IOS Press. All rights reserved.
PY - 2020/9/15
Y1 - 2020/9/15
N2 - The intention of this article is to implement a system of detection and segmentation of human silhouettes, the above mentioned tasks present a great challenge in security topics and innovation, in the last years and mainly on automated video surveillance systems, which require understanding the presence and human interaction in video sequences, e.g. Human Computer Interaction (HCI), Human Behaviour comprehension, Human fall detection, among others, but the most important is behavioural biometrics, this paper tackles the common step in these research areas: the Human silhouette extraction through the bounding box. To evaluate the proposed system, standardized databases where used and also proper videos are obtained trying to emulate real-world scenarios, where the quality and the distance are factors that have demonstrated challenges for the detection with computer vision and machine learning.
AB - The intention of this article is to implement a system of detection and segmentation of human silhouettes, the above mentioned tasks present a great challenge in security topics and innovation, in the last years and mainly on automated video surveillance systems, which require understanding the presence and human interaction in video sequences, e.g. Human Computer Interaction (HCI), Human Behaviour comprehension, Human fall detection, among others, but the most important is behavioural biometrics, this paper tackles the common step in these research areas: the Human silhouette extraction through the bounding box. To evaluate the proposed system, standardized databases where used and also proper videos are obtained trying to emulate real-world scenarios, where the quality and the distance are factors that have demonstrated challenges for the detection with computer vision and machine learning.
KW - Computer vision
KW - Human silhouette
KW - Image processing
KW - Pattern recognition
KW - R-CNN
KW - Real-Time systems
UR - http://www.scopus.com/inward/record.url?scp=85092736039&partnerID=8YFLogxK
U2 - 10.3233/FAIA200553
DO - 10.3233/FAIA200553
M3 - Contribución a la conferencia
AN - SCOPUS:85092736039
T3 - Frontiers in Artificial Intelligence and Applications
SP - 65
EP - 75
BT - Knowledge Innovation Through Intelligent Software Methodologies, Tools and Techniques - Proceedings of the 19th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2020
A2 - Fujita, Hamido
A2 - Selamat, Ali
A2 - Omatu, Sigeru
PB - IOS Press BV
T2 - 19th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2020
Y2 - 22 September 2020 through 24 September 2020
ER -