Intruder Localization and Tracking Using Two Pyroelectric Infrared Sensors

Al-Jazzar, Saleh O.; Aldalahmeh, Sami; McLernon, Des; Zaidi, Syed Ali Raza

doi:10.1109/jsen.2020.2974633

Cited by 16 publications

(9 citation statements)

References 24 publications

(27 reference statements)

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“…In our previous work [18,[20][21][22][23][24], it has already been established that the fundamental concept of dictionary learning lies in sparse representation, and the over completeness nature of the dictionary enhances the performance of sparse representation. Keeping this in mind, for the sake of making the dictionary overcomplete, each signal vector has been represented as a smaller dimensional vector consisting of Fourier coefficients by computing FFT on each dictionary atom d 𝑖 .…”

Section: Performance Evaluationmentioning

confidence: 99%

Hyperbolic function based hybrid consistent adaptive sequential DL algorithms for PIR sensor based intruder detection

Chatterjee

Rakshit

2023

J. Inst.

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This study demonstrates that a novel dictionary learning (DL) algorithm-based approach can be successfully used in conjunction with an indigenously developed hardware module, using four pyroelectric infrared (PIR) sensors, to enhance the performance of an intruder detection system. In this work, initially, a hyperbolic function based Consistent Adaptive Sequential Dictionary Learning (CAS-DL) algorithm has been proposed (HCAS-DL). Then another dictionary learning algorithm, called label consistency based K-SVD (LCK-SVD) is considered, where the label information of each dictionary atom has been introduced to enforce discriminability in sparse code. The objective function in LCK-SVD is formuated simultaneously considering the concept of label consistency (LC) constraints, reconstruction errors, and classification errors. Next, the newly proposed HCAS-DL is hybridized with LCK-SVD to form a novel version of hybrid consistent adaptive sequential dictionary learning approach, named here as the LC-HCAS-DL algorithm. Extensive experiments have been performed to establish the suitability of our proposed approach for the problem under consideration. The performance evaluation clearly establishes that the LC-HCAS-DL algorithm can achieve superior performance compared to recently proposed LC-MCAS-DL algorithm and other state-of-the-art algorithms for the intruder detection problem under consideration.

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Section: Performance Evaluationmentioning

confidence: 99%

Hyperbolic function based hybrid consistent adaptive sequential DL algorithms for PIR sensor based intruder detection

Chatterjee

Rakshit

2023

J. Inst.

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“…Al-Jazzar et. al (Al-Jazzar et al , 2020) introduced the use of signal strength of the PIR heat flux to estimate the range of an intruder and so track its trajectory. This technique uses two PIR sensors and the geometric field of views to perform this system without any extra information about the intruder’s data required.…”

Section: Previous Workmentioning

confidence: 99%

Chip-level design for intelligent human position detection based on PIR sensor

Hsia

Wang

Chen

2022

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Purpose This study aims to present a novel technique to localize the human position in a room, to manage people in a specified space. Design/methodology/approach In this study, a real-time human sensing detection and smart lighting control was designed within a single silicon core. The chip has been successfully realized within 1.5 mm2 silicon area using TSMC 0.25 um process. Findings This chip can read the weak signal of pyroelectric infrared (PIR) sensor to find the position of human body in a dark room and then help control the smart lighting system for an intelligent surveillance system. Originality/value This chip presented the retriggering delay control to expand the LED lighting time infinitely to avoid lighting-off suddenly while users stay on a space. This function is very useful in a practical intelligent surveillance system that is mainly based on human detection to better reduce power dissipation and memory space.

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“…The PIS is only capable of detecting the motion-type of human activities (i.e., activity where the person or part of their body is moving). It is not capable of detecting static human activities (e.g., when they are sitting still, standing, or laying) [ 11 ]. The thermophile IR array sensor quantifies the temperature distribution within the field of view.…”

Section: Introductionmentioning

confidence: 99%

An Infrared Array Sensor-Based Approach for Activity Detection, Combining Low-Cost Technology with Advanced Deep Learning Techniques

Arumugasamy

Bouazizi

Ohtsuki

2022

Sensors

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In this paper, we propose an activity detection system using a 24 × 32 resolution infrared array sensor placed on the ceiling. We first collect the data at different resolutions (i.e., 24 × 32, 12 × 16, and 6 × 8) and apply the advanced deep learning (DL) techniques of Super-Resolution (SR) and denoising to enhance the quality of the images. We then classify the images/sequences of images depending on the activities the subject is performing using a hybrid deep learning model combining a Convolutional Neural Network (CNN) and a Long Short-Term Memory (LSTM). We use data augmentation to improve the training of the neural networks by incorporating a wider variety of samples. The process of data augmentation is performed by a Conditional Generative Adversarial Network (CGAN). By enhancing the images using SR, removing the noise, and adding more training samples via data augmentation, our target is to improve the classification accuracy of the neural network. Through experiments, we show that employing these deep learning techniques to low-resolution noisy infrared images leads to a noticeable improvement in performance. The classification accuracy improved from 78.32% to 84.43% (for images with 6 × 8 resolution), and from 90.11% to 94.54% (for images with 12 × 16 resolution) when we used the CNN and CNN + LSTM networks, respectively.

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Intruder Localization and Tracking Using Two Pyroelectric Infrared Sensors

Cited by 16 publications

References 24 publications

Hyperbolic function based hybrid consistent adaptive sequential DL algorithms for PIR sensor based intruder detection

Hyperbolic function based hybrid consistent adaptive sequential DL algorithms for PIR sensor based intruder detection

Chip-level design for intelligent human position detection based on PIR sensor

An Infrared Array Sensor-Based Approach for Activity Detection, Combining Low-Cost Technology with Advanced Deep Learning Techniques

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