A novel architecture for dynamic integral image generation for Haar-based face detection on FPGA

2014 ◽  
Author(s):  
Chanchal Kumar ◽  
Sankalp Agarwal
Keyword(s):  
Face Detection ◽  
Image Generation ◽  
Integral Image

An Effective Method to Reduce False Alarms in Video Face Detection

2013 ◽  
Vol 347-350 ◽  
pp. 3619-3623
Author(s):  
Bing Li ◽  
Yuan Yan Tang ◽  
Di Wen ◽  
Zhen Chao Zhang ◽  
Bo Yang Ding
Keyword(s):  
Face Detection ◽  
Detection System ◽  
False Alarms ◽  
Fusion Method ◽  
Integral Image ◽  
Paper Briefly ◽  
Model Fusion ◽  
Adaboost Algorithm ◽  
Detector Structure ◽  
Face Detector

This paper briefly introduced the development of video face detection and point out the shortage of current face detection system that may produce much of false alarms. Then we detail the classic Viola face detector which using integral image, Haar-like features and AdaBoost algorithm for training. Compared with Viola face detector, we proposed an available multi-model fusion method to reduce false alarms in video face detection that is combining head-shoulder detector with HOG features. After introduced the related knowledge of HOG features, we proposed a fusion detector structure which can improve the accuracy and efficiency of detection.

Fast Pedestrian Detection for Intelligent Vehicle Based on FPGA and Monocular Vision

2013 ◽  
Vol 651 ◽  
pp. 784-788
Author(s):  
Xiao Dong Miao ◽  
Shun Ming Li ◽  
Min Xiang Wei ◽  
Huan Shen
Keyword(s):  
Detection System ◽  
Pedestrian Detection ◽  
Detection Algorithm ◽  
Intelligent Vehicle ◽  
Image Generation ◽  
Integral Image ◽  
Verilog Hdl ◽  
Adaboost Algorithm ◽  
Image Scaling ◽  
Computational Speed

This paper presents a fast pedestrian detection algorithm for intelligent vehicle based on FPGA architecture, using AdaBoost algorithm and Haar features. We describe the hardware design including image scaling, integral image generation, pipelined processing as well as classifier, and parallel processing multiple classifiers to accelerate the computational speed of the pedestrian detection system. The proposed architecture for pedestrian detection has been tested using Verilog HDL and implemented in Xilinx Virtex-5 FPGA. Its performance has been measured about 38 times than the equivalent software implementation.

scholarly journals Pendeteksi Wajah Secara Real Time pada 2 Degree of Freedom (DOF) Kepala Robot Menggunakan Deep Integral Image Cascade

CYCLOTRON ◽  
2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Dwi Agung Ayubi ◽  
Dwi Arman Prasetya ◽  
Irfan Mujahidin
Keyword(s):  
Real Time ◽  
Face Detection ◽  
Humanoid Robot ◽  
Degree Of Freedom ◽  
Raspberry Pi ◽  
Cascade Classifier ◽  
Integral Image ◽  
Haar Cascade ◽  
Time Accuracy ◽  
Face Detector

Abstrak— Teknologi Robot merupakan karya terbaik yang sangat penting bagi kehidupan manusia modern saat ini untuk mempermudah semua pekerjaan manusia. Perkembangan dunia robot saat ini akan difokuskan pada robot yang memiliki fitur mirip manusia. Bahkan diharapkan memiliki kemampuan berinteraksi dan berperilaku seperti manusia yaitu robot humanoid, mekanisme dari gerakan robot humanoid memiliki derajat kebebasan Degree of Freedom (DOF). Layaknya pada manusia robot diberi kemampuan penglihatan untuk mendeteksi adanya objek yang ditangkap secara real time Penelitian kepala robot 2 degree of freedom (DOF) untuk pendeteksi wajah secara real time menggunakan metode Deep Integral Image Cascade untuk deteksi wajahnya. Untuk keakurasian pendeteksi wajah dengan real time pada penelitian ini dengan pengujian akurasi terbesar adalah 95,25% dengan waktu respons pendeteksi tercepat 7 detik dengan waktu terlama 8,55 second rata-rata data citra semuanya tidak terdeteksi dengan benarKata kunci: Raspberry pi, Pendeteksi wajah, Degree of freedom, Haar cascade classifier, Robot kepalaAbstract— Robot technology is the best work that is very important for modern human life today to facilitate all human work. The development of the robot world today will be focused on being a robot that has human-like features. Even expected to have the ability to interact and behave like a humanoid robot, the mechanism of humanoid robot movement has a degree of freedom of Degree of Freedom (DOF). Like in the robot man is given the ability of vision to detect the presence of objects captured in real time robotic head Research 2 degree of freedom (DOF) for face detection in real time using the Deep Integral Image Cascade method to Face Detection.  For the real-time accuracy of the face detector in this research with the greatest precision testing is 95.25% with the fastest detection response time of 7 seconds with the oldest time 8.55 second the average image data everything is not detected with Really.Keywords: Raspberry Pi, face detector, Degree of freedom, Haar Cascade classifier, Robot head

scholarly journals Face Detection Using Viola Jones Algorithm

2020 ◽  
Vol 6 (11) ◽  
pp. 131-134
Author(s):  
Dherya Bengani and Prof. Vasudha Bah
Keyword(s):  
Computer Vision ◽  
Face Detection ◽  
Integral Image ◽  
Haar Features ◽  
Computer Vision Technology

Face detection is one of the most widely researched topics in recent times and is at the helm of the computer vision technology. This paper aims to review and study in detail the implementation of Viola Jones algorithm to detect faces in Realtime. Viola Jones algorithm is reviewed first followed by its main steps which include Haar features, integral image and cascading classifiers.

scholarly journals Sistem Monitoring Kehadiran Perkuliahan Menggunakan Face Detection Dengan Algoritma Viola Jones

2019 ◽  
Vol 18 (1) ◽  
pp. 119
Author(s):  
Zul Fachmi ◽  
Made Sudarma ◽  
Lie Jasa
Keyword(s):  
Face Detection ◽  
Nearest Neighbor ◽  
Cascade Classifier ◽  
Integral Image ◽  
K Nearest Neighbor

Daftar kehadiran perkuliahan adalah salah satu faktor penting pada aktivitas perkuliahan karena merupakan salah satu syarat untuk mengikuti ujian akhir semester. Pentingnya faktor kehadiran, maka diperlukan suatu sistem kehadiran dengan teknologi komputer vision yang mampu mengatasi permasalahan yang ada pada presensi secara manual. Teknologi komputer vision yang digunakan ialah pendeteksian dan pengenalan citra wajah dengan tujuan dapat memonitoring data kehadiran dari perkuliahan secara tersistem. Pada penelitian ini, proses pendeteksian wajah menggunakan algoritma Viola-Jones, adapun cara kerja dari algoritma Viola-Jones yaitu Haar Like Feature, Integral Image, Adaboost learning dan Cascade classifier. Hasil dari penelitian ini adalah algoritma Viola-Jones berhasil diterapkan pada proses pendeteksian wajah dan pada proses pengenalan citra wajah menggunakan metode KNN (K-Nearest Neighbor) dengan tingkat keakurasian sebesar 94.79%.

A Facial Recognition System Based on Integral Image

2014 ◽  
Vol 687-691 ◽  
pp. 3905-3908
Author(s):  
Wei Xin Zhang ◽  
Wei Bing Bai ◽  
Chao Xu ◽  
Wei Yuan Chen ◽  
Rui Jiang
Keyword(s):  
Face Detection ◽  
Recognition System ◽  
Integral Image ◽  
Image Capture ◽  
Identification Rate ◽  
Development Framework ◽  
Detection Program ◽  
The Face ◽  
Facial Recognition System ◽  
Hardware Circuit

This article made a in-depth research of the face detection with the method of integral image, which is based on image capture and recognition technology, and designed the hardware circuit and software program development framework. Designed hardware circuit platform around the Cortex-A8 core processor in hardware, which was exclusively for the camera driver, face recognition and image capture. Prorammed face detection code with QT, and finally transplanted the face detection program to ARM board. Results show that the system has a high identification rate correctly and a good real-time performance under normal lighting conditions after a certain sample size of the test.

scholarly journals Building Face Detection with Face Divine Proportions

2021 ◽  
Vol 17 (04) ◽  
pp. 63
Author(s):  
Mohamed Oualla ◽  
Khalid Ounachad ◽  
Abdelalim Sadiq
Keyword(s):  
Face Detection ◽  
Face Image ◽  
Integral Image ◽  
Detection Rates ◽  
Aesthetic Medicine ◽  
Adaboost Algorithm ◽  
The World ◽  
High Detection ◽  
The Face ◽  
Human Faces

<p class="0abstract"><span lang="EN-US">In this paper, we proposed an algorithm for detecting multiple human faces in an image based on haar-like features to represent the invariant characteristics of a face. The choice of relevant and more representative features is based on the divine proportions of a face. This technique, widely used in the world of beauty, especially in aesthetic medicine, allows the face to be divided into a set of specific regions according to known mathematical measures. Then we used the Adaboost algorithm for the learning phase. All of our work is based on the Viola and Jones algorithm, in particular their innovative technique called Integral Image, which calculates the value of a Haar-Like feature extracted from a face image. In the rest of this article, we will show that our approach is promising and can achieve high detection rates of up to 99%.</span></p>

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