|
|
Object Detection on GPU
Macenauer, Pavel ; Polok, Lukáš (referee) ; Juránek, Roman (advisor)
This thesis addresses the topic of object detection on graphics processing units. As a part of it, a system for object detection using NVIDIA CUDA was designed and implemented, allowing for realtime video object detection and bulk processing. Its contribution is mainly to study the options of NVIDIA CUDA technology and current graphics processing units for object detection acceleration. Also parallel algorithms for object detection are discussed and suggested.
|
|
|
Mobile App for Measuring the Range from the Preceding Vehicle in Traffic
Henry, Andrii ; Zemčík, Pavel (referee) ; Herout, Adam (advisor)
This master's thesis deals with development of mobile app for measuring the range from the preceding vehicle in traffic using visual-based methods. This paper describes implementation of computer vision algorithms of detection and tracing objects, detection of horizon on desktop and mobile devices. Also deals with visual-based range measuring without any other mechanisms. The output of the work is implemented detectors of vihicles and horizon using OpenCV library on the Windows platfom and draft of user inerface of a mobile phone aplication on the Android platform.
|
|
|
Object Detection on GPU
Jurák, Martin ; Hradiš, Michal (referee) ; Juránek, Roman (advisor)
This thesis is focused on the acceleration of Random Forest object detection in an image. Random Forest detector is an ensemble of independently evaluated random decision trees. This feature can be used to acceleration on graphics unit. Development and increasing performance of graphics processing units allow the use of GPU for general-purpose computing (GPGPU). The goal of this thesis is describe how to implement Random Forest method on GPU with OpenCL standard.
|
|
|
Tabletop Object Detection
Varga, Tomáš ; Zemčík, Pavel (referee) ; Španěl, Michal (advisor)
This work describes the issue of tabletop object detection in point cloud. Point cloud is recorded with Kinect sensor. Designed solution uses algorithm RANSAC for plane detection, algorithm Euclidean clustering for segmentation and ICP algorithm for object detection. Algorithm ICP is modified and mainly it can detect rotational symetric objects and objects without any transformation against it's models. The final package is build on platform ROS. The achieved results with own dataset are good despite of the limited functionality of the detector.
|
|
|
Linux user interface using camera
Dolníček, Petr ; Beneš, Radek (referee) ; Šmirg, Ondřej (advisor)
The goal of this was to create a fully functional program coded in C++, which is capable of real time object detection and mouse positioning in operating system Linux. Object detection is based on recognizing desired color and shape from webcam input. In this case it was a red circle. The main part of source code was generated via application Harpia. This is an application especially created for purposes of object tracking, border detection and picture processing. Most of used functions belong to OpenCV library. This library, as well as Harpia application, was created for computer vision, so it has many functions especially for purposes of my program. You can find many information about edge detection, color filtering and noise reduction in this document. I have also managed to control mouse cursor according to data that program detects. My program fulfils its purpose.
|
|
|
Path monitoring
Sedlařík, Jan ; Janáková, Ilona (referee) ; Richter, Miloslav (advisor)
This bachelor's thesis deals with path monitoring theme. To successful accomplishment of this task it is right to have the high-quality videos. It is imperative to concentrate to their correct scanning and preprocessing. Detection of objects and their monitoring are one of the most elementary parts of the challenge. Important part of image separation is edge detection.
|
|
|
Image object detection using template
Novák, Pavel ; Mašek, Jan (referee) ; Burget, Radim (advisor)
This Thesis is focused to Image Object Detection using Template. Main Benefit of this Work is a new Method for sympthoms extraction from Histogram of Oriented Gradients using set of Comparators. In this used Work Methods of Image comparing and Sympthoms extraction are described. Main Part is given to Histogram of Oriented Gradients Method. We came out from this Method. In this Work is used small training Data Set (100 pcs.) verified by X-Validation, followed by tests on real Sceneries. Achieved success Rate using X-Validation is 98%. for SVM Algorithm.
|
|
|
Image object detector based on C4 algorithm
Vylíčil, Radek ; Rajmic, Pavel (referee) ; Mašek, Jan (advisor)
This thesis deals with the image object detection using Contour cues. The text describes methods how to train and test object detector. The main contribution of this thesis consists in creation Feature extractor for creation object detector in Java programming. The functionality of object detector was demonstrated on medical images.
|
|
|
The idnetification of the objects in the imege
Zavalina, Viktoriia ; Fliegel, Karel (referee) ; Boleček, Libor (advisor)
Master´s thesis deals with methods of objects detection in the image. It contains theoretical, practical and experimental parts. Theoretical part describes image representation, the preprocessing image methods, and methods of detection and identification of objects. The practical part contains a description of the created programs and algorithms which were used in the programs. Application was created in MATLAB. The application offers intuitive graphical user interface and three different methods for the detection and identification of objects in an image. The experimental part contains a test results for an implemented program.
|
|
|
Object tracking in videosequence
Nešpor, Zdeněk ; Zukal, Martin (referee) ; Číka, Petr (advisor)
This thesis deals with tracking a predefined object in the movie. After a brief introduction describes the procedure suitable for the detection of an object in a video sequence, where the methods are also discussed in detail. There is dealt with issues of image preprocessing, image segmentation and object detection in the image. The main emphasis is laid on using detectors of interest points and descriptors of areas - SURF and SIFT. The second part deals with the practical implementation of a program suitable to monitor predefined object in the movie. First are analyzed libraries suitable for object tracking in a video sequence in an environment of Java, followed by a detailed description of the selected library OpenCV along with wrapper JavaCV. Further described is own application in terms of control and functionality are described key method. Outputs along with discussion and evaluation are presented at the end of work.
|
guest ::
