[Technical Notice] GV-AI Guard PVD Motion Detection Usage and Case Studies
Posted: June 2nd, 2023, 2:39 pm
Article ID: GV2-23-06-2
Release Date: June 2, 2023
Applied to
GV-AI Guard V1.1
Introduction
False alarms have long plagued security personnel, making false alarm reduction a top priority for surveillance systems. Person and Vehicle Detection (PVD) in GV-AI Guard uses deep-learning algorithms to provide more robust and accurate motion detection than traditional motion detection approaches.
Although PVD significantly advances motion detection capabilities, achieving 100% accuracy remains challenging due to the inherent complexities and uncertainties of real-world environments. The PVD algorithms use several detection thresholds to determine detection sensitivity and filter out false positives. You can fine-tune these thresholds to optimize PVD motion detection accuracy and performance for your specific cameras and applications.
This document includes case studies on fine-tuning PVD motion detection, alongside details on the latest software patch designed to improve PVD motion detection performance.
For details, see the technical notice: GV-AI Guard PVD Motion Detection Usage and Case Studies
Latest Software Patch
With the latest patch V1.1.0.2, you can now adjust the detection thresholds. The patch is only applicable to GV-AI Guard V1.1.
GV-AI Guard patch V1.1.0.2 download: https://dlcdn.geovision.com.tw/Software ... .1.0.2.zip
Release Date: June 2, 2023
Applied to
GV-AI Guard V1.1
Introduction
False alarms have long plagued security personnel, making false alarm reduction a top priority for surveillance systems. Person and Vehicle Detection (PVD) in GV-AI Guard uses deep-learning algorithms to provide more robust and accurate motion detection than traditional motion detection approaches.
Although PVD significantly advances motion detection capabilities, achieving 100% accuracy remains challenging due to the inherent complexities and uncertainties of real-world environments. The PVD algorithms use several detection thresholds to determine detection sensitivity and filter out false positives. You can fine-tune these thresholds to optimize PVD motion detection accuracy and performance for your specific cameras and applications.
This document includes case studies on fine-tuning PVD motion detection, alongside details on the latest software patch designed to improve PVD motion detection performance.
For details, see the technical notice: GV-AI Guard PVD Motion Detection Usage and Case Studies
Latest Software Patch
With the latest patch V1.1.0.2, you can now adjust the detection thresholds. The patch is only applicable to GV-AI Guard V1.1.
GV-AI Guard patch V1.1.0.2 download: https://dlcdn.geovision.com.tw/Software ... .1.0.2.zip