The paper presents an approach to localize human body joints in 3D coordinates based on a single low resolution depth image. First a framework to generate a database of 80k realistic depth images from a 3D body model ...
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ISBN:
(纸本)9788362065301
The paper presents an approach to localize human body joints in 3D coordinates based on a single low resolution depth image. First a framework to generate a database of 80k realistic depth images from a 3D body model is described. Then data preprocessing and normalization procedure, and DNN and MLP artificial neural networks architectures and training are presented. The robustness against camera distance and image noise is analysed. Localization accuracy for each joint is reported and application for low resolution and large distance pose estimation is proposed. A very fast regression on body joints locations in 3D space is achieved, even in case of sensor noise, large distance and reaching off the screen.
In this paper two approaches to upscaling of low resolution bitmaps created using pixel art digital form are proposed. The methods are aimed to deal with limitations of classical and dedicated algorithms typically use...
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ISBN:
(纸本)9788362065301
In this paper two approaches to upscaling of low resolution bitmaps created using pixel art digital form are proposed. The methods are aimed to deal with limitations of classical and dedicated algorithms typically used in gaming applications. The proposed spatial methods, proximity-based coefficient correction and transition area restriction, lead to no limitations in scale factor in comparison to the existing pixel-art algorithms. Moreover, in contrast to the classical methods the proposed approaches allow to obtain undistorted and sharp resulting images.
Qmazda is a package of software tools for digital image analysis. They compute shape, color and texture attributes in arbitrary regions of interest, implement selected algorithms of discriminant analysis and machine l...
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ISBN:
(纸本)9788362065301
Qmazda is a package of software tools for digital image analysis. They compute shape, color and texture attributes in arbitrary regions of interest, implement selected algorithms of discriminant analysis and machine learning, and enable texture based image segmentation. The algorithms generalize a concept of texture to three-dimensional data to enable analysis of volumetric images from magnetic resonance imaging or computed tomography scanners. The tools support a complete workflow from image examples as an input to classification rules as an output. The extracted knowledge can be further used in custom made image analysis systems. Here we also present an application of QMaZda to identify defective barley kernels. The cereal seeds variability is high, therefore, characterization and discriminant analysis of such the biological objects is challenging and non-trivial. The software is available free of charge and open source, with executables for Windows, Linux and OS X platforms.
This paper sets out and presents a new approach to determine the stroke volume of the artificial ventricle. The stroke volume of the chamber is one of the basic heart function parameters. For the artificial heart assi...
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ISBN:
(纸本)9788362065301
This paper sets out and presents a new approach to determine the stroke volume of the artificial ventricle. The stroke volume of the chamber is one of the basic heart function parameters. For the artificial heart assist purpose, in the study this value is calculated based on the mapped shape of the flaccid membrane of the extracorporeal pneumatic heart assist pump. This is a continuation of the earlier work on the use of imageprocessing and analysis techniques to determine the membrane shape and the stroke volume of an artificial ventricle. The study focused on the determining the stroke volume using the numerical integration method. To do this, the membrane shape in the actual dimensions in millimetres is first mapped, and then a double integral under this surface is calculated. The comparison of different ways of numerical integration for different sizes of the measurement matrix as well as the obtained results were presented.
This session features papers focusing on imageprocessing algorithms, self-learning reconfiguration management and fault tolerance for reconfigurable systems.
This session features papers focusing on imageprocessing algorithms, self-learning reconfiguration management and fault tolerance for reconfigurable systems.
Many researchers use convolutional neural networks with small rectangular filters for music (spectrograms) classification. First, we discuss why there is no reason to use this filters setup by default and second, we p...
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ISBN:
(纸本)9781509041176
Many researchers use convolutional neural networks with small rectangular filters for music (spectrograms) classification. First, we discuss why there is no reason to use this filters setup by default and second, we point that more efficient architectures could be implemented if the characteristics of the music features are considered during the design process. Specifically, we propose a novel design strategy that might promote more expressive and intuitive deep learning architectures by efficiently exploiting the representational capacity of the first layer - using different filter shapes adapted to fit musical concepts within the first layer. The proposed architectures are assessed by measuring their accuracy in predicting the classes of the Ballroom dataset. We also make available1 the used code (together with the audio-data) so that this research is fully reproducible.
Background subtraction is one of the fundamental steps in the image-processing pipeline for distinguishing foreground from background. Most of the methods have been investigated with respect to visual images, in which...
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ISBN:
(纸本)9781538618424
Background subtraction is one of the fundamental steps in the image-processing pipeline for distinguishing foreground from background. Most of the methods have been investigated with respect to visual images, in which case challenges are different compared to thermal images. Thermal sensors are invariant to light changes and have reduced privacy concerns. We propose the use of a low-pass IIR filter for background modelling in thermographic imagery due to its better performance compared to algorithms such as Mixture of Gaussians and K-nearest neighbour, while reducing memory requirements for implementation in embedded architectures. Based on the analysis of four different image datasets both indoor and outdoor, with and without people presence, the learning rate for the filter is set to 3x10-3 Hz and the proposed model is implemented on an Artix-7 FPGA.
This paper presents a pedestrian detection system with enhanced object segmentation procedure working on a far infrared (FIR) video. To make the object detection more accurate on the FIR images, we propose an enhanced...
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ISBN:
(纸本)9788362065301
This paper presents a pedestrian detection system with enhanced object segmentation procedure working on a far infrared (FIR) video. To make the object detection more accurate on the FIR images, we propose an enhanced segmentation procedure with two thresholds and the region enlargement. This combination allowed a significant reduction of the region of interests (ROIs) for further processing. Experiments performed on demanding public dataset show a significant increase of the pedestrian detection performance (up to 33 frames per second) with the accuracy comparable with state-of-the-art algorithms.
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