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Particle filter based single shot multibox detector for human moving prediction
Maharani D.A.a, Machbub C.a, Yulianti L.a, Rusmin P.H.a
a School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2020 IEEEMoving object tracking has become a center of attention for computer vision researchers. It is quite challenging to track a moving object correctly, especially when the object has occlusion, changes in illumination, unexpected movements, and arbitrary poses. To enhance the accuracy of the moving object detector, we proposed SSD (Single Shot Multibox Detector) in addition to PF (Particle Filter) to provide prediction of moving human. Performance evaluation was done with the comparison to the previously proposed HOG-SVM as a detector. The proposed system has been successfully tested in two videos. PF based SSD with 100 particles performs well, with RMSE 7.44 and 91.24 effective particle. The results show that the addition of SSD in measurement process could enhance the PF’s performance to track moving human. The results have also shown that the proposed method was successfully implemented in combination with a specific color detection to track a specific human object.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]A-center,Color detection,Measurement process,Moving object tracking,Moving objects,Particle filter,Single shots[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Detection,HOG-SVM,Particle Filter,Specific color detection,SSD,Tracker[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]ACKNOWLEDGMENT This research is a part of Penelitian Disertasi Doktor (PDD) Dikti funded by Layanan Beasiswa dan Pendanaan Riset Indonesia (LPDP) 2020.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICSET51301.2020.9265355[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]