A Soft-YoloV4 for High-Performance Head Detection and Counting

Blockage of pedestrians will cause inaccurate people counting, and people’s heads are easily blocked by each other in crowded occasions. To reduce missed detections as much as possible and improve the capability of the detection model, this paper proposes a new people counting method, named Soft-Yol...
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Autor*in:	Zhen Zhang [verfasserIn] Shihao Xia [verfasserIn] Yuxing Cai [verfasserIn] Cuimei Yang [verfasserIn] Shaoning Zeng [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	head detection YoloV4 NMS soft-NMS people counting

Übergeordnetes Werk:	In: Mathematics - MDPI AG, 2013, 9(2021), 23, p 3096
Übergeordnetes Werk:	volume:9 ; year:2021 ; number:23, p 3096

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/math9233096

Katalog-ID:	DOAJ054036607

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language	English
source	In Mathematics 9(2021), 23, p 3096 volume:9 year:2021 number:23, p 3096
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authorswithroles_txt_mv	Zhen Zhang @@aut@@ Shihao Xia @@aut@@ Yuxing Cai @@aut@@ Cuimei Yang @@aut@@ Shaoning Zeng @@aut@@
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topic	misc QA1-939 misc head detection misc YoloV4 misc NMS misc soft-NMS misc people counting misc Mathematics
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title	A Soft-YoloV4 for High-Performance Head Detection and Counting
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title_auth	A Soft-YoloV4 for High-Performance Head Detection and Counting
abstract	Blockage of pedestrians will cause inaccurate people counting, and people’s heads are easily blocked by each other in crowded occasions. To reduce missed detections as much as possible and improve the capability of the detection model, this paper proposes a new people counting method, named Soft-YoloV4, by attenuating the score of adjacent detection frames to prevent the occurrence of missed detection. The proposed Soft-YoloV4 improves the accuracy of people counting and reduces the incorrect elimination of the detection frames when heads are blocked by each other. Compared with the state-of-the-art YoloV4, the AP value of the proposed head detection method is increased from 88.52 to 90.54%. The Soft-YoloV4 model has much higher robustness and a lower missed detection rate for head detection, and therefore it dramatically improves the accuracy of people counting.
abstractGer	Blockage of pedestrians will cause inaccurate people counting, and people’s heads are easily blocked by each other in crowded occasions. To reduce missed detections as much as possible and improve the capability of the detection model, this paper proposes a new people counting method, named Soft-YoloV4, by attenuating the score of adjacent detection frames to prevent the occurrence of missed detection. The proposed Soft-YoloV4 improves the accuracy of people counting and reduces the incorrect elimination of the detection frames when heads are blocked by each other. Compared with the state-of-the-art YoloV4, the AP value of the proposed head detection method is increased from 88.52 to 90.54%. The Soft-YoloV4 model has much higher robustness and a lower missed detection rate for head detection, and therefore it dramatically improves the accuracy of people counting.
abstract_unstemmed	Blockage of pedestrians will cause inaccurate people counting, and people’s heads are easily blocked by each other in crowded occasions. To reduce missed detections as much as possible and improve the capability of the detection model, this paper proposes a new people counting method, named Soft-YoloV4, by attenuating the score of adjacent detection frames to prevent the occurrence of missed detection. The proposed Soft-YoloV4 improves the accuracy of people counting and reduces the incorrect elimination of the detection frames when heads are blocked by each other. Compared with the state-of-the-art YoloV4, the AP value of the proposed head detection method is increased from 88.52 to 90.54%. The Soft-YoloV4 model has much higher robustness and a lower missed detection rate for head detection, and therefore it dramatically improves the accuracy of people counting.
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