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Pulse Visualization in Videosequence of Face
Bernátek, Pavel
Eulerian video magnification method may be used for visualization of the pulse in the videosequence of face. This article describes its utilization with combination of Viola-Jones face detection algorithm and Kanade-Lucas-Tomasi algorithm for tracking faces in the videosequence.
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Pulse visualization in videosequence of face
Bernátek, Pavel ; Potočňák, Tomáš (referee) ; Janoušek, Oto (advisor)
In the semestral thesis is given basic methods of non-contact measurement heart rate. There is explained Eulerian video magnification method deals with the visualization of the pulse in the videosequence of face. The semestral thesis describes algorithm Viola-Jones face detection in images and algorithm Kanade-Lucas-Tomasi for tracking faces in the videosequence. Part of the work includes design and realization of measurement. There is explained realization of the program and documented execution results, which are discussed. From the results it is designed to guide for optimal recording.
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Image processing using Android device
Korchakov, Sergei ; Richter, Miloslav (referee) ; Honec, Peter (advisor)
This master’s Thesis focuses on image processing on Android platform and development of an application, that is able to do face detection and recognition in real scene. Thesis gives highlight of modern algorithms of face detection. It first examines and compares the standard features of Android platform (FaceDetector a FaceDetectionListener) and JJIL, OpenIMAJ, OpenCV libraries experiment, and presents the results. For purposes of face recognition was selected OpenCV library. Three different algorithms of identification were tested: FisherFaces, EigenFaces a Local Binary Patterns Histograms. Based on performance comparison best methods were implemented in developed application.
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Biometrics using Face Recognition
Koupil, Michal ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
This work is focused on a face detection in a picture and subsequent recognition of the face in its respective database. Face detection had been implemented using Viola-Jones algorithm. To recognize the face afterwards, PCA (Principal Component Analysis) a LBPH (Local Binary Pattern Histograms) had been used. Implemented algorithm had been tested on freely accesible biometric databases. Overall success rate of face detection was 93,4 %. Overall success rate of face recognition using PCA was 88,1 % and with LBPH it was 93,1 %. Of the two methods for face recognition, LBPH method has better ability to perform recognition with data, that do not possess ideal parameters for biometrics. With data suitable for biometrics, both of the methods perform well, with PCA being faster.
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Biometrics using face recognition
Koupil, M. ; Odstrčilík, J.
This paper is focused on a face detection in a picture and subsequent recognition of the face in its respective database. Face detection had been implemented using Viola-Jones algorithm. To recognize the face afterwards, PCA had been used. Implemented algorithm had been tested on freely accessible biometric databases.
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Biometrics using Face Recognition
Koupil, Michal ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
This work is focused on a face detection in a picture and subsequent recognition of the face in its respective database. Face detection had been implemented using Viola-Jones algorithm. To recognize the face afterwards, PCA (Principal Component Analysis) a LBPH (Local Binary Pattern Histograms) had been used. Implemented algorithm had been tested on freely accesible biometric databases. Overall success rate of face detection was 93,4 %. Overall success rate of face recognition using PCA was 88,1 % and with LBPH it was 93,1 %. Of the two methods for face recognition, LBPH method has better ability to perform recognition with data, that do not possess ideal parameters for biometrics. With data suitable for biometrics, both of the methods perform well, with PCA being faster.
|
|
|
Pulse Visualization in Videosequence of Face
Bernátek, Pavel
Eulerian video magnification method may be used for visualization of the pulse in the videosequence of face. This article describes its utilization with combination of Viola-Jones face detection algorithm and Kanade-Lucas-Tomasi algorithm for tracking faces in the videosequence.
|
|
|
Pulse visualization in videosequence of face
Bernátek, Pavel ; Potočňák, Tomáš (referee) ; Janoušek, Oto (advisor)
In the semestral thesis is given basic methods of non-contact measurement heart rate. There is explained Eulerian video magnification method deals with the visualization of the pulse in the videosequence of face. The semestral thesis describes algorithm Viola-Jones face detection in images and algorithm Kanade-Lucas-Tomasi for tracking faces in the videosequence. Part of the work includes design and realization of measurement. There is explained realization of the program and documented execution results, which are discussed. From the results it is designed to guide for optimal recording.
|
|
|
Image processing using Android device
Korchakov, Sergei ; Richter, Miloslav (referee) ; Honec, Peter (advisor)
This master’s Thesis focuses on image processing on Android platform and development of an application, that is able to do face detection and recognition in real scene. Thesis gives highlight of modern algorithms of face detection. It first examines and compares the standard features of Android platform (FaceDetector a FaceDetectionListener) and JJIL, OpenIMAJ, OpenCV libraries experiment, and presents the results. For purposes of face recognition was selected OpenCV library. Three different algorithms of identification were tested: FisherFaces, EigenFaces a Local Binary Patterns Histograms. Based on performance comparison best methods were implemented in developed application.
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