AdaLine: Adaptive Optimizing Counting Lines in Object-Detection-Tracking Systems

AdaLine: Adaptive Optimizing Counting Lines in Object-Detection-Tracking Systems

Combining object detection, tracking, and counting has become a widely-used method. The position and angle of cameras can vary according to the deployment scenarios, both of which affect object counting. In current practice, we have to set the position of the counting line manually. However, determi...

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Bibliographic Details
Published in:2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) pp. 413 - 416
Main Authors: Huang, Wenhao, Nakazawa, Jin
Format: Conference Proceeding
Language:English
Published: IEEE 11-03-2024
Subjects:
Adaptive systems
Cameras
Conferences
counting algorithm
image processing
object counting
Object detection
object tracking
Optimization
Pervasive computing
Sensors
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Summary:Combining object detection, tracking, and counting has become a widely-used method. The position and angle of cameras can vary according to the deployment scenarios, both of which affect object counting. In current practice, we have to set the position of the counting line manually. However, determining the optimal position for each scenario remains a challenge. In this paper, we propose the AdaLine, an adaptive optimization algorithm for object counting lines in detection-tracking-counting sensing systems. AdaLine calculates the movement characteristics of objects to automatically generate a counting line suitable for deployment scenarios. By using the driving recorder video data taken from real buses, we experimentally evaluate the sensing performance of the proposed algorithm and verify that our proposed algorithm improves counting accuracy.
ISSN:2766-8576
DOI:10.1109/PerComWorkshops59983.2024.10503429