The realization of face detection and fullness detection in medium by using Haar Cascade Classifiers

Savaş, Burcu Kır; İlkin, Sümeyya; Becerikli, Yaşar

doi:10.1109/siu.2016.7496215

Cited by 12 publications

(4 citation statements)

References 7 publications

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“…The eye and face detection module was programmed with the modified feature-based Haar cascade face detection classifier algorithm [15,19,21,22]. The modified Haar cascade face detection classifier algorithm detects an edge, line, and center-surround features of an intruder object.…”

Section: Methodologies and Results Analysismentioning

confidence: 99%

Smart Home Anti-Theft System: A Novel Approach for Near Real-Time Monitoring, Smart Home Security and Large Video Data Handling for Wellness Protocol

Pandya¹,

Ghayvat²,

Kotecha³

et al. 2018

Preprint

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Abstract:The proposed research methodology aims to design a generally implementable framework for providing a house owner/member with the immediate notification of an on-going theft (unauthorized access to their premises). For this purpose, a rigorous analysis of existing systems was undertaken to identify research gaps. The problems found with existing systems were that they can only identify the intruder after the theft, or cannot distinguish between human and non-human objects. Wireless Sensors Networks (WSNs) combined with the use of Internet of Things (IoT), Cognitive Internet of Things, Internet of Medical Things, and Cloud Computing are expanding smart home concepts and solutions, and their applications. The primary objective of the present research work was to design and develop IoT and cloud computing based smart home solutions. In addition, we also propose a novel smart home anti-theft system that can detect an intruder, even if they have partially/fully hidden their face using clothing, leather, fiber, or plastic materials. The proposed system can also detect an intruder in the dark using a CCTV camera without night vision facility. The fundamental idea was to design a cost-effective and efficient system for an individual to be able to detect any kind of theft in real-time and provide instant notification of the theft to the house owner. The system also promises to implement home security with large video data handling in real-time.

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Section: Methodologies and Results Analysismentioning

confidence: 99%

Smart Home Anti-Theft System: A Novel Approach for Near Real-Time Monitoring, Smart Home Security and Large Video Data Handling for Wellness Protocol

Pandya¹,

Ghayvat²,

Kotecha³

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Haar cascade algorithm: Viola and Jones proposed the algorithm that utilizes edge or line location highlights in their exploration paper "Rapid Object Detection using a Boosted Cascade of Simple Features" issued in the year 2001 [12]. The algorithm is trained using a ton of positive and negative pictures consisting of faces and no faces, respectively [13].…”

Section: Face Detectionmentioning

confidence: 99%

A Proposed Framework for Identity Verification in Passport Management Using Model Scaling and Semantic Similarity

Khurana,

Bhatia,

Battan

et al. 2023

ISI

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The dependence on images for face detection and identity verification was at odds with broad assessment which showed that coordinating with sets of non-similar images was profoundly inclined to make mistakes. The current passport management lacks security of data and requires more manpower and time, manual calculations, and verification of documents as well as the photographs. Additionally, the computerized passport examination requires accurate processing in order to carry out crucial tasks like identifying passport forgeries, looking for wanted criminals, or finding those who are ineligible for immigration, among other things because the utilization of fake passports addresses a huge danger to the security of the nation. Therefore, the purpose of this paper is to enhance the identity verification process in passport management. The paper comprises implementation of various technologies and technology driven models for serving its purpose by using the latest and efficient techniques that includes neural networks, face detection, image similarity, ROI (region of interest) and model scaling. The dataset utilized in the paper was self-prepared by the authors and consisted of 5 images each for 10 different individuals. It had been trained from scratch on different models based on CNN architecture. Out of all the three models used for training, the model that resulted in highest accuracy was further considered for research. EfficientNetB0 resulted in 82% accuracy being the highest out of all the three models. The threshold for the model was thereby calculated using z-score which compared the similarity scores and classified the images as similar or non-similar. Therefore, it can be concluded that the techniques utilized in the paper are efficient enough to determine the similarity of an image with its corresponding image.

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“…We can train our own classifier for any object like table, book, car, etc. using OpenCV [13,19]. But, in this project we only need to detect face for cropping the images.…”

Section: Haar Cascadementioning

confidence: 99%

Drowsiness Detection System for Online Courses

Lahoti¹

2020

IJATCSE

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Online courses are gaining currency these days. But they aren't as effective as classroom teaching. Hence, we designed an application to make the online courses interactive. A drowsiness detection system is implemented which uses the concept of Ear Aspect Ratio and Mouth Aspect Ratio and it is validated using ResNet50 pre-trained model. Once the course attendee is detected drowsy, questions are generated using Natural Language Processing based on the video watched till then. If the attendee answers the question incorrectly a penalty would be imposed, else the video resumes. The highest training accuracy achieved was 97% and highest validation accuracy achieved was 94%.

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The realization of face detection and fullness detection in medium by using Haar Cascade Classifiers

Cited by 12 publications

References 7 publications

Smart Home Anti-Theft System: A Novel Approach for Near Real-Time Monitoring, Smart Home Security and Large Video Data Handling for Wellness Protocol

Smart Home Anti-Theft System: A Novel Approach for Near Real-Time Monitoring, Smart Home Security and Large Video Data Handling for Wellness Protocol

A Proposed Framework for Identity Verification in Passport Management Using Model Scaling and Semantic Similarity

Drowsiness Detection System for Online Courses

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