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Semiautomatic Collection of Large Database of Human Faces
Michalík, Marek ; Hradiš, Michal (referee) ; Herout, Adam (advisor)
The project is focused on methods of obtaining large number of images of human faces. Such database should then serve as a set of data for face detection and recognition by the means of supervised machine learning. The work deals with the basic principles of supervised machine learning and available data sets for this procedure. Project contains proposals of techniques and implementation of algorithms suitable for acquiring images from video and a concept of user interface for semi-automatic acceptation and annotation of located images.
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Video-Based Human-Computer Interface
Chrápek, David ; Švub, Miroslav (referee) ; Španěl, Michal (advisor)
This bachelor´s thesis is focused on video-based human-computer interface controlled by movement of the whole head. By tracking relative positions of eyes and nose angles of head are determined and by movement of head simple gestures are recognized. For image processing Haar-cascades based on Viola-Jones of classifiers were used to recognize head, eyes and nose within the image and for their tracking mainly Lucas-Kanade optical flow method was used.
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Face recognition
Maňkoš, Richard ; Mézl, Martin (referee) ; Kolář, Radim (advisor)
This diploma thesis deals with face recognition in digital pictures. The first part describes biometry and, shortly, characterizes biometrical methods which are the most oftenly used. In the second part is described the approach of face recognition in a picture. Specifically, it is described the method for face detection - Viola-Jones and method for face recognition - PCA, which will be implemented in Matlab. The last part, which is practical, describes the scheme for video-sequence recording, implementation of the PCA method in Matlab and discussion of the achieved results.
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Real time face recognizer
Juráček, Aleš ; Přinosil, Jiří (referee) ; Richter, Miloslav (advisor)
My diploma thesis deals about face detection in picture. I try to outline problems of computer vision, artificial intelligence and machine learning. I described in details the proposed detection by Viola and Jones, which uses AdaBoost learning algorithm. This method was deliberately chosen for speed and detection accuracy. This detector was made in programming language C / C + + using the OpenCV library. To a final learning was used database of faces images „MIT CVCL Face Database“. The main goal was to propose the face detector utilizable also in video-sequences.
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Object detection
Vítek, Pavel ; Kratochvíla, Lukáš (referee) ; Richter, Miloslav (advisor)
This paper deals with object detection where a human figure is used as a model. The introductory chapter defines terms detection and object. The second chapter describes the basic theory of computer vision , such as image processing and its parts. A substantial part is also focused on the Canny edge detection, upper body detection and pose detection. The third chapter describes the MATLAB integrated development environment in which the image processing functions are implemented. The last chapter is a practical demonstration of object detection. Different upper body detection methods are compared there. In the last subsection, two methods of determining the deviations based on the template are compared. Finally, all methods are compared with respect to the obtained results.
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Automatic People Counting from Panoramic Photography
Blucha, Ondřej ; Kolář, Martin (referee) ; Veľas, Martin (advisor)
This bachelor thesis deals with automatic people counting from panoramic photography. This is very useful for counting large number of people, such as on the stadium or on the concerts. It consists of the two parts. The first one is image stitching, which process the images by the feature-based methods. The second part is people counting using face detection, where were used Viola-Jones detector. The ideal setting of parameters for used methods was experimentally selected.
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Smartphone Game Using Recognition of Face Features
Skoták, Jiří ; Szőke, Igor (referee) ; Herout, Adam (advisor)
This master's thesis focuses on smartphone game for iOS, which uses recognition of face features and other information, which can be obtained from a smartphone's camera and sensors. This work describes a few approaches for real-time face detection and then introduces and compares possibilities for such task on iOS. Moreover, the thesis contains a draft of the final game and its levels. The game showcases various technologies in its levels such as object detection, processing an image color and others. Finally, the thesis introduces the final form of the game that is released and available on the App Store.
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Object detection
Vítek, Pavel ; Kratochvíla, Lukáš (referee) ; Richter, Miloslav (advisor)
This paper deals with object detection where a human figure is used as a model. The introductory chapter defines terms detection and object. The second chapter describes the basic theory of computer vision , such as image processing and its parts. A substantial part is also focused on the Canny edge detection, upper body detection and pose detection. The third chapter describes the MATLAB integrated development environment in which the image processing functions are implemented. The last chapter is a practical demonstration of object detection. Different upper body detection methods are compared there. In the last subsection, two methods of determining the deviations based on the template are compared. Finally, all methods are compared with respect to the obtained results.
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Smartphone Game Using Recognition of Face Features
Skoták, Jiří ; Szőke, Igor (referee) ; Herout, Adam (advisor)
This master's thesis focuses on smartphone game for iOS, which uses recognition of face features and other information, which can be obtained from a smartphone's camera and sensors. This work describes a few approaches for real-time face detection and then introduces and compares possibilities for such task on iOS. Moreover, the thesis contains a draft of the final game and its levels. The game showcases various technologies in its levels such as object detection, processing an image color and others. Finally, the thesis introduces the final form of the game that is released and available on the App Store.
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