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Face Detection

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Face detection is a computer vision task that involves identifying and locating human faces within digital images or video streams. It utilizes algorithms and machine learning techniques to analyze visual data, enabling applications such as facial recognition, emotion detection, and human-computer interaction.
lightbulbAbout this topic
Face detection is a computer vision task that involves identifying and locating human faces within digital images or video streams. It utilizes algorithms and machine learning techniques to analyze visual data, enabling applications such as facial recognition, emotion detection, and human-computer interaction.

Key research themes

1. How do cascading classifiers enhance both efficiency and accuracy in face detection systems?

Cascading classifiers are pivotal in face detection for rapidly discarding non-face regions while focusing computational resources on probable face candidates. This theme investigates various cascading approaches, feature selection mechanisms, and classifier architectures that balance speed and detection accuracy. Understanding these methods is critical for real-time applications where computational resources are limited but high reliability is required.

Key finding: Introduced the integral image representation enabling fast feature computation and a cascaded classifier structure that achieves face detection at 15 frames per second with high detection rates. The cascade discards over 50%... Read more
Key finding: Compared several cascading classifiers — Dynamic Cascade, Haar Cascade, SURF cascade, and Fea-Accu cascade — quantitatively analyzing their detection accuracy and rejection rates. Found that methods like the Fea-Accu cascade... Read more
Key finding: Implemented face detection with Haarcascade classifiers alongside LBPH for recognition in an automated attendance system, demonstrating practical viability of cascading classifiers in institutional settings. The system... Read more

2. What are the critical facial features and geometric relationships utilized for reliable face detection under varying conditions?

Identifying consistent facial features and leveraging geometric relationships among them allows face detection systems to be robust against pose, expression, occlusion, and lighting changes. This theme explores how specific features—such as eyes and mouth—and their spatial configurations, including geometric structures like isosceles triangles, contribute to accurate detection and verification in challenging scenarios.

Key finding: Through perceptual rating experiments on face-like inanimate objects generating pareidolia, identified eyes and mouth as the critical local features most significantly influencing faceness perception. The study’s regression... Read more
Key finding: Proposed an innovative face detection method using geometric configurations based on the spatial relationship of two eyes and one mouth forming an isosceles triangle. This geometric rule enables the system to extract... Read more

3. How do deep learning and classical dimensionality reduction methods compare and complement each other in face detection and recognition?

This theme examines the performance of modern deep learning-based face detection architectures against classical approaches like Principal Component Analysis (PCA) and Eigenfaces, focusing on trade-offs between computational efficiency, accuracy, scalability, and applicability to real-world variable environments. It also considers advances in lightweight CNNs for face-related tasks and highlights hybrid strategies that integrate classical and modern methods for improved performance in constrained settings.

Key finding: Presented a deep learning framework, based on VGG16 and RetinaNet, optimized for detecting small faces under challenging conditions like occlusion, blur, and scale variation. The approach merges high-level and low-level... Read more
Key finding: Developed a PCA and Eigenfaces-based face recognition pipeline that efficiently reduces dimensionality and extracts discriminative facial features. Demonstrated robustness across lighting, pose, and expression variations with... Read more
Key finding: Designed an efficient face recognition model combining Modified-Local Difference Binary descriptors with an extreme gradient boosting classifier, providing robustness to pose, expression, scale, and illumination changes.... Read more

All papers in Face Detection

Agricultural Development combined with technology has made great progress in recent years, making it possible to improve the yield for farmers. This project combines deep learning algorithms with spraying technology to design a machine... more
Attendance for the students is a key task in class. When done by calling roll numbers, it generally wastes the productive time of class. This proposed solution for the current problem is through automation of the attendance system using... more
The Facial Action Coding System (FACS) is an objective method for quantifying facial movement in terms of 44 component actions, i.e. Action Units (AUs). This system is widely used in behavioral investigations of emotion, cognitive process... more
Web lectures have many positive aspects, e.g. they enable learners to easily control the learning experiences). To develop high-quality online learning materials takes a lot of time and human efforts . An alternative is to develop a... more
Within the last couple of years, automatic multimodal recognition of human emotions has gained a considerable interest from the research community. By taking into account more sources of information, the multimodal approaches allow for... more
This paper discusses our expert system called Integrated System for Facial Expression Recognition (ISFER), which performs recognition and emotional classification of human facial expression from a still full-face image. The system... more
The Facial Action Coding System (FACS) is an objective method for quantifying facial movement in terms of 44 component actions, ie Action Units (AUs). This system is widely used in behavioral investigations of emotion, cognitive process... more
This report is based on a project did by Robalge Sankalpana Sewmini Lenora of Plymouth University third-year student. This report presents the development and implementation of a face recognition-based attendance system designed to... more
Cardio Vascular Diseases (CVDs) pose an important global health challenge, contributing substantially to mortality rates worldwide. Electrocardiography (ECG) is a necessary diagnostic tool in the detection of CVDs. Manual analysis by... more
OpenCV, YOLO and FaceNet. once an individual is found, the system identifies the person. His identity are remodeled to audio and introduced to the user. Similarly, regionally found objects are conferred in audio format to the user.
The research focuses on creating an automated attendance system using face recognition through the Convolutional Neural Network (CNN) approach at IPB University's Vocational School. The current manual attendance methods show limitations,... more
Nowadays, face detection plays important roles in many applications, such as: human-computer interaction, security and surveillance, face recognition etc. In this paper, a novel scheme for human face detection in color images under... more
During the last few years, Local Binary Patterns (LBP) has aroused increasing interest in image processing and computer vision. LBP was originally proposed for texture analysis, and has proved a simple yet powerful approach to describe... more
The crime rate has been rising at an unprecedented rate, and security has become a big concern in ATM machines. Face detection is the most common biometric technique due to its non-invasive nature. It's been used in a variety of fields,... more
This study presents the design and implementation of a low-cost object-detecting night vision device based on the Raspberry Pi platform for integration with small arms used by the Armed forces. The system employs an infrared... more
The primary target of content based image retrieval is to return a list of images that are most similar to a query image. This is usually done by ordering the images based on a similarity score. In most state-of-the-art systems, the... more
Although many face detection algorithms have been introduced in the literature, only a handful of them can meet the real-time constraints of mobile devices. This paper presents the real-time implementation of our previously introduced... more
Conventional attendance recording methods, are susceptible to delays, impersonation, and hygiene concerns. This paper presents a realtime attendance monitoring system tailored for educational environments where accuracy, and record... more
The Intelligent Surveillance Support System(ISSS) is an innovative software solution that enables real-time monitoring and analysis of security footage to detect and identify potential threats. This system incorporates advanced features... more
Coronavirus Disease 2019 (COVID-19) has spread all over the world since it broke out massively in December 2019, which has caused a large loss to the whole world. Both the confirmed cases and death cases have reached a relatively... more
Face recognition systems play a crucial role in security, surveillance, and authentication applications. However, traditional deep learning-based models, particularly Convolutional Neural Networks (CNNs), often struggle with issues such... more
Face is the crucial part of the human body that uniquely identifies a person. Using the face characteristics as biometric, the face recognition system can be implemented. The most demanding task in any organization is attendance marking.... more
The Covid 19 (coronavirus) pandemic has become one of the most lethal health crises worldwide. This virus gets transmitted from a person by respiratory droplets when they sneeze or when they speak. According to leading and well-known... more
Driver drowsiness is implicated in up to 30% of traffic accidents worldwide, and timely alerts can save lives.However, current detection systems often trigger false alarms during normal behavior-such as rapid glances or conversational... more
The objective of the attendance system is to provide an alternative means to the traditional attendance system which consumes 10 to 15 minutes of time in 50 minutes of lecture hour. It also aims at eliminating human errors and proxy in... more
The electronic structure of Ba3Ta6Si4O26 was calculated using the generalized gradient approximation (GGA). The band gap of Ba3Ta6Si4O26 was theoretically estimated to be 2.92 eV. Both of the upper valence and lower conduction bands... more
This paper presents the application of evolutionary multi-objective optimization (EMO) to the improvement of a face detection system. The face detection system is based on the boosted cascade system, and analyzes image positions on... more
In this paper we perform a study of the image contents of the Chilean web (.cl domain) using automatic feature extraction, content-based analysis and face detection algorithms. In an automated process we examine all .cl websites and... more
This review paper examines the integration of Explainable AI (XAI) techniques into abnormal human activity detection from surveillance videos, emphasizing their significance in enhancing transparency, accountability, and trustworthiness... more
The paper introduces the problem of robust head detection in collaborative learning environments. In such environments, the camera remains fixed while the students are allowed to sit at different parts of a table. Example challenges... more
This paper reports on an analysis of the Hart Inter-Civic DAU eSlate unit equipped for disabled access and the associated Judge's Booth Controller. The analysis examines whether the eSlate and JBC can be subverted to compromise the... more
This paper reports on an analysis of the Hart Inter-Civic DAU eSlate unit equipped for disabled access and the associated Judge's Booth Controller. The analysis examines whether the eSlate and JBC can be subverted to compromise the... more
This paper discusses the development of employee attendance recording system with face recognition. The system to identify the employee by comparing the detected face image with already registered images in the system database and save... more
This paper presents a system for real-time facemask recognition, integrating automation through deep learning to enhance public health measures and mitigate the spread of infectious diseases. The proposed system employs OpenCV's Haar... more
Head detection and localization are one of the most investigated and demanding tasks of the Computer Vision community. These are also a key element for many disciplines, like Human Computer Interaction, Human Behavior Understanding, Face... more
Head detection and localization is a demanding task and a key element for many computer vision applications, like video surveillance, Human Computer Interaction and face analysis. The stunning amount of work done for detecting faces on... more
Computer Vision enables mobile devices to extract the meaning of the observed scene from the information acquired with the onboard sensor cameras. Nowadays, there is a growing interest in Computer Vision algorithms able to work on mobile... more
We undertook a study to determine if the automatic detection and counting of vehicle passengers is feasible. An automated passenger counting system would greatly facilitate the operation of freeway lanes reserved for car-pools (HOV... more
The development of a face recognition-based attendance monitoring system for educational institutions is the main objective of this automated attendance management system based on facial recognition. This will update and improve the... more
In this paper we present a collection of C and C++ biometric performance benchmark algorithms called FacePerf. The benchmark includes three different face recognition algorithms that are historically important to the face recognition... more
Color compatibility is the essence of fashion and dress selection, not only determining the beauty of an outfit but also determining consumer purchasing behavior. Following the significance of visually pleasing and harmonious garments,... more
As more people start using the Internet and more content is placed online, the chances that individuals will encounter inappropriate or unwanted adult-oriented content increases. This paper presents a practical and scalable method to... more
This paper presents a method based on AdaBoost to identify the sex of a person from a low resolution grayscale picture of their face. The method described here is implemented in a system that will process well over 10 9 images. The goal... more
As more people start using the Internet and more content is placed online, the chances that individuals will encounter inappropriate or unwanted adult-oriented content increases. This paper presents a practical and scalable method to... more
In this paper, we present a neural network-based face detection system. Unlike similar systems which are limited to detecting upright, frontal faces, this system detects faces at any degree of rotation in the image plane. The system... more
This paper presents a method based on AdaBoost to identify the sex of a person from a low resolution grayscale picture of their face. The method described here is implemented in a system that will process well over 10 9 images. The goal... more
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