Dual PTZ cameras approach for security face detection

Nguyen, Trung Hai; Bui, Hieu Minh; Nguyen, Son; Hoang, Hong X; Pham, Thanh V.; Souza-Daw, Tony de

doi:10.1109/cce.2014.6916751

Cited by 6 publications

(6 citation statements)

References 16 publications

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“…The narrow-view camera was then cued (through the mentioned coordinate transformation) to actively collect high-resolution images of the targets whose resolution was lower than the defined threshold. The accuracy of the overall target detection system was thus much improved [ 2 ]. Cui et al also proposed a binocular system using two PTZ cameras.…”

Section: Introductionmentioning

confidence: 99%

Active Multimodal Sensor System for Target Recognition and Tracking

Zhang

Zou

et al. 2017

Sensors

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High accuracy target recognition and tracking systems using a single sensor or a passive multisensor set are susceptible to external interferences and exhibit environmental dependencies. These difficulties stem mainly from limitations to the available imaging frequency bands, and a general lack of coherent diversity of the available target-related data. This paper proposes an active multimodal sensor system for target recognition and tracking, consisting of a visible, an infrared, and a hyperspectral sensor. The system makes full use of its multisensor information collection abilities; furthermore, it can actively control different sensors to collect additional data, according to the needs of the real-time target recognition and tracking processes. This level of integration between hardware collection control and data processing is experimentally shown to effectively improve the accuracy and robustness of the target recognition and tracking system.

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Section: Introductionmentioning

confidence: 99%

Active Multimodal Sensor System for Target Recognition and Tracking

Zhang

Zou

et al. 2017

Sensors

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“…Commercial face recognition system is used for recognition. This system can detect faces at distances of 25-50 m and recognize faces (first successful face recognition) at distances of 15-20 m. This type of camera systems is also used in [7], [8]. The second approach is to design a face recognition system for images captured at various distances.…”

Section: Introductionmentioning

confidence: 99%

Designing a Low-Resolution Face Recognition System for Long-Range Surveillance

Peng

Spreeuwers

Veldhuis

2016

2016 International Conference of the Biometrics Special Interest Group (BIOSIG)

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Most face recognition systems deal well with highresolution facial images, but perform much worse on lowresolution facial images. In low-resolution face recognition, there is a specific but realistic surveillance scenario: a surveillance camera monitoring a large area. In this scenario, usually the gallery images are of high-resolution and the probe images are of various low-resolutions depending on the distances between the subject and the camera. In this paper, we design a low-resolution face recognition system for this scenario. We use a state-ofthe-art mixed-resolution classifier to deal with the resolution mismatch between the gallery and probe images. We also set up experiments to explore the best training configuration for probe images of various resolutions. Our experimental results show that one classifier which is trained on images of various resolutions covering the whole range has promising results in the long-range surveillance scenario. This system has at least as good performance as combining multiple face recognition systems that are optimised for different resolutions.

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“…There are two approaches to deal with this situation. The first one is to improve acquisition devices so that the images captured at the farthest distance have a high enough resolution for recognition [16][17][18]. The second approach is to design a face recognition system for images captured at various distances, but there is only a limited number of publications on this topic [19,20].…”

Section: Approaches To Low-resolution Face Recognitionmentioning

confidence: 99%

“…A commercial face recognition software is used for recognition. This system can detect faces at distances of 25-50 m and recognize faces (first successful face recognition) at distances of 15-20 m. This type of camera systems is also used in [17,18]. The second approach is to design a face recognition system for images captured at various distances.…”

Section: Introductionmentioning

confidence: 99%

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Face Recognition at a Distance

Peng¹

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Dual PTZ cameras approach for security face detection

Cited by 6 publications

References 16 publications

Active Multimodal Sensor System for Target Recognition and Tracking

Active Multimodal Sensor System for Target Recognition and Tracking

Designing a Low-Resolution Face Recognition System for Long-Range Surveillance

Face Recognition at a Distance

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