Pedestrian detection
30. August 2015

This project focuses on preprocessing of training images for pedestrian detection. The goal is to train a model of a pedestrian detection. Histogram of oriented gradients HOG has been used as descriptor of image features. Support vector machine SVM has … Continue reading

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Detection of objects in soccer
22. April 2015

Lukas Sekerak Project idea Try detect objects (players, soccer ball, referees, goal keeper) in soccer match. Detect their position, movement and show picked object in ROI area. More info in a presentation and description document. Requirements Opencv 2.4 log4cpp Dataset … Continue reading

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Stereo reconstruction
23. February 2015

Ondrej Galbavy This example presents straightforward process to determine depth of points (sparse depth map) from stereo image pair using stereo reconstruction. Example is implemented in Python 2. Stereo calibration process We need to obtain multiple stereo pairs with chessboard … Continue reading

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Motion Analysis & Object Tracking

Pavol Zbell Introduction In our work we focus on basics of motion analysis and object tracking. We compare MeanShift (non-parametric, finds an object on a back projection image) versus CamShift (continuously adaptive mean shift, finds an object center, size, and … Continue reading

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Signature recognition

Matej Stetiar Main purpose of this project was to recognise signatures. For this purpose we used descriptor from the bottom of the signature. Then we used Mahalanobis distance to identify signatures. Image preprocessing We have worked with 2 sets of … Continue reading

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Tracking moving object

This example shows how to separate and track moving object using OpenCV. First, the background of the video is being calculated and moving objects detected, then it is filtered and tracked. Used: cv::BackgroundSubtractorMOG2; cv::getStructuringElement; cv::morphologyEx; cv::BackgroundSubtractorMOG2.operator(); The process Initialize the … Continue reading

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Object removing in image/video

Marek Grznar Introduction In our project we focus on simple object recognition, then tracking this recognized object and finally we try to delete this object from video. By object recognition we used local features-based methods. We compare SIFT and SURF … Continue reading

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Local Descriptors in OpenCv

Tomas Martinkovic The project shows detection of chocolate cover from input image or frame of video. For each video or image may be chosen various combinations of detector with descriptor. For matching object of chocolate cover with input frame or image automatically … Continue reading

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Smile detection

Jan Podmajersky Smile detection is a popular feature of today’s photo cameras. It is not implemented in all cameras, as a popular face detection, because it is more complicated to implement. This project shows a basic algorihtm in the topic. It may … Continue reading

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SIFT in RGB-D (Object recognition)

Marek Jakab In this example we focus on enhancing the current SIFT descriptor vector with additional two dimensions using depth map information obtained from kinect device. Depth map is used for object segmentation (see: http://vgg.fiit.stuba.sk/2013-07/object-segmentation/) as well to compute standard … Continue reading

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Fire detection in video

Stefan Linner The main aim of this example is to automatically detect fire in video, using computer vision methods, implemented in real-time with the aid of the OpenCV library. Proposed solution must be applicable in existing security systems, meaning with … Continue reading

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Eye-Shape Classification

Veronika Štrbáková The project shows detection and recognition of face and eyes from input image (webcam). I use for detection and classification haarcascade files from OpenCV. If eyes are recognized, I classify them as opened or narrowed. The algorithm uses … Continue reading

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