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State machine implementation for human object tracking using combination of mobilenet, KCF tracker, and HOG features
Kinasih F.M.T.R.a, Saragih C.F.D.a, Machbub C.a, Rusmin P.H.a, Yulianti L.a, Andriana D.b
a Bandung Institute of Technology, Indonesia
b Indonesian Institute of Sciences, 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, School of Electrical Engineering and Informatics. All rights reserved.Since the Viola and Jones’ method on real-time face detection was proposed in 2001, numerous works for object detection, person recognition, and object tracking have been published by papers and journals. Each method has its strong points and drawbacks. That means that in a system which only employs a standalone method, we could only get either speed or accuracy. In this paper, we proposed a state-machine method to combine face recognition, face detection, and tracker to harness the tracker promptness while maintaining the ability to distinguish the person of interest with the other person and backgrounds, to overcome the limitations of the standalone method. Subsequently, the information gathered from this image processing side will be delivered to the hardware tracker. The image processing side becomes a visual sensor that provides feedback or measurement value i.e. center point coordinate value from the detected face. The 2 DOF hardware tracker camera platform being used implements Model Predictive Control to calculate required control action thus the platform is able to track the target object, keeping it at the center of the frame. MPC method is chosen because it produces an optimal control signal while considering the input signal saturation aspect. The MPC control signals deliver a good control pan and tilt system response with rise time < 1 second and overshoot <15%. It is also noticed that the FSM implemented in this paper is able to meet the goal with a considerable performance for indoor settings.[/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][/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]Computer vision,MPC,Pan-tilt camera,Person recognition,State machine,Tracker,Visual servoing[/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]This research is a part of Research, Community Services, and Innovation program (Program Penelitian, Pengabdian kepada Masyarakat dan Inovasi/P3MI) funded by the Institute for Research and Community Services at the Institut Teknologi Bandung (LPPM ITB).[/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/10.15676/ijeei.2019.11.4.5[/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]