Face Detection and Recognition Using Raspberry PI Computer

This paper presents a face detection and recognition system utilizing a Raspberry Pi computer that is built on a predefined framework. The theoretical section of this article shows several techniques that can be used for face detection, including Haar cascades, Histograms of Oriented Gradients, Support Vector Machine and Deep Learning Methods. The paper also provides examples of some commonly used face recognition techniques, including Fisherfaces, Eigenfaces, Histogram of Local Binary Patterns, SIFT and SURF descriptor-based methods and Deep Learning Methods. The practical aspect of this paper demonstrates use of a Raspberry Pi computer, along with supplementary tools and software, to detect and recognize faces using a pre-defined dataset

Face detection and recognition using Raspberry Pi

Ovim radom će se prikazati sustav za detekciju lica, te prepoznavanje lica iz unaprijed definirane baze koristeći Raspberry Pi računalo. Za detekciju lica mogu se koristiti različiti algoritmi poput Haarovih kaskada (Viola - Jones), histogrami orijentiranih gradijenata (HOG), metode potpornih vektora (SVM), te metode dubokog učenja koji će u teoretskom dijelu biti prikazani. Kao nastavak biti će prikazane neke postojeće metode koje se koriste za prepoznavanje lica poput Fisherfaces, Eigenfaces, histogrami lokalnih binarnih uzoraka, metode temeljene na SIFT i SURF deskriptorima i metode dubokog učenja zajedno sa primjerima koda u Python programskom jeziku. Kao završni dio ovog rada biti će prikazan praktični dio, odnosno uporaba Raspberry Pi računala sa pripadajućom opremom i programskom podrškom u svrhu detekcije i prepoznavanja lica uz pomoć unaprijed definirane baze.This paper will show a face detection system, and face recognition from a predefined database using a Raspberry Pi computer. Different algorithms can be used for face detection, such as Haar cascades (Viola - Jones), oriented gradient histograms (HOG), support vector methods (SVM), and deep learning methods, which will be presented in the theoretical part. As a continuation, some existing methods used to recognize faces will be presented such as Fisherfaces, Eigenfaces, histograms of local binary patterns, methods based on SIFT and SURF descriptors and deep learning methods along with code examples in Python programming language. As the final part of this paper, the practical part will be presented, ie the use of Raspberry Pi computers with associated equipment and software for the purpose of face detection and recognition with the help of a predefined database

Face detection and recognition using Raspberry Pi

Ovim radom će se prikazati sustav za detekciju lica, te prepoznavanje lica iz unaprijed definirane baze koristeći Raspberry Pi računalo. Za detekciju lica mogu se koristiti različiti algoritmi poput Haarovih kaskada (Viola - Jones), histogrami orijentiranih gradijenata (HOG), metode potpornih vektora (SVM), te metode dubokog učenja koji će u teoretskom dijelu biti prikazani. Kao nastavak biti će prikazane neke postojeće metode koje se koriste za prepoznavanje lica poput Fisherfaces, Eigenfaces, histogrami lokalnih binarnih uzoraka, metode temeljene na SIFT i SURF deskriptorima i metode dubokog učenja zajedno sa primjerima koda u Python programskom jeziku. Kao završni dio ovog rada biti će prikazan praktični dio, odnosno uporaba Raspberry Pi računala sa pripadajućom opremom i programskom podrškom u svrhu detekcije i prepoznavanja lica uz pomoć unaprijed definirane baze.This paper will show a face detection system, and face recognition from a predefined database using a Raspberry Pi computer. Different algorithms can be used for face detection, such as Haar cascades (Viola - Jones), oriented gradient histograms (HOG), support vector methods (SVM), and deep learning methods, which will be presented in the theoretical part. As a continuation, some existing methods used to recognize faces will be presented such as Fisherfaces, Eigenfaces, histograms of local binary patterns, methods based on SIFT and SURF descriptors and deep learning methods along with code examples in Python programming language. As the final part of this paper, the practical part will be presented, ie the use of Raspberry Pi computers with associated equipment and software for the purpose of face detection and recognition with the help of a predefined database

Face Detection and Recognition Using Raspberry PI Computer

This paper presents a face detection and recognition system utilizing a Raspberry Pi computer that is built on a predefined framework. The theoretical section of this article shows several techniques that can be used for face detection, including Haar cascades, Histograms of Oriented Gradients, Support Vector Machine and Deep Learning Methods. The paper also provides examples of some commonly used face recognition techniques, including Fisherfaces, Eigenfaces, Histogram of Local Binary Patterns, SIFT and SURF descriptor-based methods and Deep Learning Methods. The practical aspect of this paper demonstrates use of a Raspberry Pi computer, along with supplementary tools and software, to detect and recognize faces using a pre-defined dataset