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Article

Enhancing Multi-Camera People Detection by Online Automatic Parametrization Using Detection Transfer and Self-Correlation Maximization

Video Processing and Understanding Laboratory (VPULab), Universidad Autónoma de Madrid, 28049 Madrid, Spain
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This paper is an extended version of our paper published in García-Martín, A.; SanMiguel, J.C. Adaptive people detection based on cross-correlation maximization. In Proceedings of the 2017 IEEE International Conference on Image Processing (ICIP), Beijing, China, 17–20 September 2017.
These authors contributed equally to this work.
Sensors 2018, 18(12), 4385; https://doi.org/10.3390/s18124385
Received: 5 November 2018 / Revised: 7 December 2018 / Accepted: 8 December 2018 / Published: 11 December 2018
(This article belongs to the Section Intelligent Sensors)
Finding optimal parametrizations for people detectors is a complicated task due to the large number of parameters and the high variability of application scenarios. In this paper, we propose a framework to adapt and improve any detector automatically in multi-camera scenarios where people are observed from various viewpoints. By accurately transferring detector results between camera viewpoints and by self-correlating these transferred results, the best configuration (in this paper, the detection threshold) for each detector-viewpoint pair is identified online without requiring any additional manually-labeled ground truth apart from the offline training of the detection model. Such a configuration consists of establishing the confidence detection threshold present in every people detector, which is a critical parameter affecting detection performance. The experimental results demonstrate that the proposed framework improves the performance of four different state-of-the-art detectors (DPM , ACF, faster R-CNN, and YOLO9000) whose Optimal Fixed Thresholds (OFTs) have been determined and fixed during training time using standard datasets. View Full-Text
Keywords: self-correlation maximization; multi-camera; people detection; automatic parametrization self-correlation maximization; multi-camera; people detection; automatic parametrization
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MDPI and ACS Style

Martín-Nieto, R.; García-Martín, Á.; Martínez, J.M.; SanMiguel, J.C. Enhancing Multi-Camera People Detection by Online Automatic Parametrization Using Detection Transfer and Self-Correlation Maximization . Sensors 2018, 18, 4385. https://doi.org/10.3390/s18124385

AMA Style

Martín-Nieto R, García-Martín Á, Martínez JM, SanMiguel JC. Enhancing Multi-Camera People Detection by Online Automatic Parametrization Using Detection Transfer and Self-Correlation Maximization . Sensors. 2018; 18(12):4385. https://doi.org/10.3390/s18124385

Chicago/Turabian Style

Martín-Nieto, Rafael, Álvaro García-Martín, José M. Martínez, and Juan C. SanMiguel 2018. "Enhancing Multi-Camera People Detection by Online Automatic Parametrization Using Detection Transfer and Self-Correlation Maximization " Sensors 18, no. 12: 4385. https://doi.org/10.3390/s18124385

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