TY - JOUR
T1 - A Weight Joint-Based Clustering (WJC) method for secure monitoring system
AU - Jin, Y.
AU - Alsadoon, Abeer
AU - Prasad, P. W.C.
AU - Singh, A. K.
AU - Elchouemi, A.
N1 - Includes bibliographical references.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Currently, 3D depth sensors are used in monitoring systems to give accurate results in identifying objects. The existing monitoring systems which use 3D sensors are effective in recognizing object gestures, but do not consider an object's change in location. This paper proposes a new system that uses a 3D camera sensor and weight joint-based in clustering method to identify objects' change in location and to recognize object activities, using a 3D camera to capture the depth value of an object in order to measure its location with the aid of position data of the object's joints. Because the system uses depth value to identify the object's location, it does not require any extra processes for improving the accuracy of clustering where the object is available. The system provides 100% accuracy when recognizing objects' activities has low processing time and is cost effective.
AB - Currently, 3D depth sensors are used in monitoring systems to give accurate results in identifying objects. The existing monitoring systems which use 3D sensors are effective in recognizing object gestures, but do not consider an object's change in location. This paper proposes a new system that uses a 3D camera sensor and weight joint-based in clustering method to identify objects' change in location and to recognize object activities, using a 3D camera to capture the depth value of an object in order to measure its location with the aid of position data of the object's joints. Because the system uses depth value to identify the object's location, it does not require any extra processes for improving the accuracy of clustering where the object is available. The system provides 100% accuracy when recognizing objects' activities has low processing time and is cost effective.
KW - Activity recognition
KW - Clustering method
KW - Weight joint-based method
UR - http://www.scopus.com/inward/record.url?scp=85040700897&partnerID=8YFLogxK
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U2 - 10.1016/j.procs.2017.12.082
DO - 10.1016/j.procs.2017.12.082
M3 - Review article
AN - SCOPUS:85040700897
SN - 1877-0509
VL - 125
SP - 640
EP - 646
JO - Procedia Computer Science
JF - Procedia Computer Science
ER -