|
|
Human-Machine Interface Based on Gestures
Charvát, Jaroslav ; Beran, Vítězslav (referee) ; Bartoň, Radek (advisor)
Master's thesis "Human-Machine Interface Based on Gestures" depicts the theoretical background of the computer vision and gesture recognition. It describes more in detail different methods that were used to create the application. Practical part of this thesis consists of the description of the developed program and its functionality. Using this application, user should be able to control computer by gestures of both right and left hands and also his head. The program is primarily based on the skin detection that is followed by the recognition of palms and head gestures. There were used two essential methods for these actions, AdaBoost and PCA.
|
|
|
Searching for Points of Interest in Raster Image
Kaněčka, Petr ; Sumec, Stanislav (referee) ; Herout, Adam (advisor)
This document deals with an image points of interest detection possibilities, especially corner detectors. Many applications which are interested in computer vision needs these points as their necessary step in the image processing. It describes the reasons why it is so useful to find these points and shows some basic methods to find them. There are compared features of these methods at the end.
|
|
|
AdaBoost in Computer Vision
Hradiš, Michal ; Zemčík, Pavel (referee) ; Potúček, Igor (advisor)
In this thesis, we present the local rank differences (LRD). These novel image features are invariant to lighting changes and are suitable for object detection in programmable hardware, such as FPGA. The performance of AdaBoost classifiers with the LRD was tested on a face detection dataset with results which are similar to the Haar-like features which are the state of the art in real-time object detection. These results together with the fact that the LRD are evaluated much faster in FPGA then the Haar-like features are very encouraging and suggest that the LRD may be a solution for future hardware object detectors. We also present a framework for experiments with boosting methods in computer vision. This framework is very flexible and, at the same time, offers high learning performance and a possibility for future parallelization. The framework is available as open source software and we hope that it will simplify work for other researchers.
|
|
|
Scene Analysis Based on the 2D Images
Hejtmánek, Martin ; Drahanský, Martin (referee) ; Orság, Filip (advisor)
This thesis deals with an object surface analysis in a simple scene represented by two-dimensional raster image. It summarizes the most common methods used within this branch of information technology and explains both their advantages and drawbacks. It introduces the design of an surface profile analysis algorithm based on the lighting analysis using knowledge and experiences from previous work. It contains a detailed description of the implemented algorithm and discusses the experimental results. It also brings up options for the possible enhancement of the projected algorithm.
|
|
|
Hand Motion Recognition
Blaho, Juraj ; Beran, Vítězslav (referee) ; Hradiš, Michal (advisor)
The aim of this work is to design and implement a novel computer interface based on detection and tracking of a hand in an image from a single camera. The created interface doesn't require any special hardware and it is possible to use it on a common computer with standard web-camera. The implemented interface was used to create an application, which is able to synthesize keyboard and mouse input events and this way it is able to control existing programs without the need to change their source code. Another contribution of this work is a novel method of automatic data acquisition for training of hand detectors. By using this method it is possible to collect thousands of training examples in a few hours.
|
|
|
Automatic Photography Categorization
Gajová, Veronika ; Hradiš, Michal (referee) ; Španěl, Michal (advisor)
Purpose of this thesis is to design and implement a tool for automatic categorization of photos. The proposed tool is based on the Bag of Words classification method and it is realized as a plug-in for the XnView image viewer. The plug-in is able to classify a selected group of photos into predefined image categories. Subsequent notation of image categories is written directly into IPTC metadata of the picture as a keyword.
|
|
|
The API of a Video and Image Datastore
Fröml, Vojtěch ; Volf, Tomáš (referee) ; Zendulka, Jaroslav (advisor)
This master's thesis proposes and implements an extension of the database interface VTApi which is being developed as a part of the MV ČR project "Tools and methods for video and image processing for terrorism prevention" at FIT VUT. This interface provides support for representation, management and indexation of multimedia data and related descriptive metadata used by analytic applications based on computer vision. It currently uses DBMS PostgreSQL as its default datastore. Paper describes basic techniques for processing image and video data, VTApi concept and proposes and implements its modifications for the purpose of supporting multiple types of datastores. As an example of an alternative datastore, support for usage of a SQLite database is integrated into VTApi.
|
|
| |
|
|
Graphics and Video Algorithms in GP-GPU
Kula, Michal ; Polok, Lukáš (referee) ; Zemčík, Pavel (advisor)
This diploma thesis is focused on object detections through general-purpose computing on graphics processor units. There is an explanation of graphics adapters work and basics of their architecture in this thesis. Based on the adapters, there is the effective work in libraries for general-purpose computing on graphics processor units demonstrated in this thesis. Further, the thesis shows the available algorithms for object detection and which ones from them are possible to be effectively parallelized. In conclusion of this thesis, there is a comparison of the object detections speeds to common implementations on classical processors.
|
|
|
Detection of the Cars Approaching the Crossroad
Hopjan, Tomáš ; Peringer, Petr (referee) ; Rozman, Jaroslav (advisor)
This project deals with monitoring cars approaching the crossroads. Describes various methods of detection and discussing their problems. Primary goal is surveillance during the day in different weather conditions, but method of detection cars during the night and low light is also introduced. The most widely used algorithms are implemented using the OpenCV library. Important part is testing different algorithms and also variety of lighting conditions, camera locations and settings.
|
guest ::
