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Human Localization With Multi-Camera Using Detection And Tracking Object
Winardi S.a, Akbar S.b, Dwi Wardhana Y.b
a STMIK STIE Mikroskil, Department Of Information Technology, Medan, Indonesia
b School of Electrical Engineering and Informatics, Bandung Institute of Technology (ITB), 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]© 2019 IEEE.Object location determination in a room is a system which can determine the position of an object or person in a physical room. Localization systems which have been built using wireless sensor networks such as RFID, GPS, or Cellular networks are considered less effective. Hence, the present camera usage system as low-cost position determination will be developed. This system consists of two processes which are single-camera processing and multi-camera processing. In single-camera processing, we present object detection using Multi-Scale Spectral Residual (MSR) preprocessing to obtain camera position and best enviroment condition which will be used in multi-camera processing. In multi-camera processing, the object location detection result in the single camera will be combined and tracked in the room floor plan. From the experiment, the result is that human localization efficiency in room is 87.07% in average with minimum error accuracy is 0.02 meter and maximum error accuracy is 2.2 meter.[/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]Histogram of Oriented,Homographies,Human Tracking,Localizaton,Multi-Scale Spectral Residual,Weighting error[/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]Bias Weighting Error,Histogram of Oriented,Homography,Human Tracking,Localizaton,Multi-Scale Spectral Residual[/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][/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/ICIC47613.2019.8985756[/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]