This article presents an optimized algorithm for Nonnegative Tensor Factorization (NTF), implemented in the CUDA (Compute Uniform Device Architecture) framework, that runs on contemporary graphics ...processors and exploits their massive parallelism. The NTF implementation is primarily targeted for analysis of high-dimensional spectral images, including dimensionality reduction, feature extraction, and other tasks related to spectral imaging; however, the algorithm and its implementation are not limited to spectral imaging. The speedups measured on real spectral images are around 60 - 100× compared to a traditional C implementation compiled with an optimizing compiler. Since common problems in the field of spectral imaging may take hours on a state-of-the-art CPU, the speedup achieved using a graphics card is attractive. The implementation is publicly available in the form of a dynamically linked library, including an interface to MATLAB, and thus may be of help to researchers and engineers using NTF on large problems.
Light field rendering is an image-based rendering method that does not use 3D models but only images of the scene as input to render new views. Light field approximation, represented as a set of ...images, suffers from so-called refocusing artifacts due to different depth values of the pixels in the scene. Without information about depths in the scene, proper focusing of the light field scene is limited to a single focusing distance. The correct focusing method is addressed in this work and a real-time solution is proposed for focusing of light field scenes, based on statistical analysis of the pixel values contributing to the final image. Unlike existing techniques, this method does not need precomputed or acquired depth information. Memory requirements and streaming bandwidth are reduced and real-time rendering is possible even for high resolution light field data, yielding visually satisfactory results. Experimental evaluation of the proposed method, implemented on a GPU, is presented in this paper.
Image compression has been one of the main research topics in the field of image processing for a long time. The research usually focuses on compressing images that are visible to humans. The images ...being compressed are usually gray-level images or RGB color images. Recent advances in technology, however, enable the authors to make the detailed processing of spectral features in the images. Therefore, the compression of images with many spectral channels, called multispectral images, is required. Many methods used in traditional lossy image compression can be reused also in the compression of multispectral images. In this paper, a new combination of clustering spectra, manipulating spectral vectors, and encoding and decoding for multispectral images is presented. In the manipulation of the spectral vectors PCA, ICA, and wavelets are used. The approach is based on extracting relevant spectral information. Furthermore, some quantitative quality measures for multispectral images are presented.
We investigate whether recently high and consequently rapidly decreasing U.S. house prices have been justified by fundamental factors such as personal income, population, house rent, stock market ...wealth, building costs, and mortgage rate. We first conduct the standard unit root and cointegration tests with aggregate data. Nationwide analysis potentially suffers from problems of the low power of stationarity tests and the ignorance of dependence among regional house markets. Therefore, we also employ
panel data stationarity tests which are robust to cross-sectional dependence. Contrary to previous panel studies of the U.S. housing market, we consider several, not just one, fundamental factors. Our results confirm that panel data unit root tests have greater power as compared with univariate tests. However, the overall conclusions are the same for both methodologies. The house price does not align with the fundamentals in sub-samples prior to 1996 and from 1997 to 2006. It appears that the real estate prices take long swings from their fundamental value and it can take decades before they revert to it. The most recent correction (a collapsed bubble) occurred around 2006.
Reduced-rank restrictions can add useful parsimony to coefficient matrices of multivariate models, but their use is limited by the daunting complexity of the methods and their theory. The present ...work takes the easy road, focusing on unifying themes and simplified methods. For Gaussian and non-Gaussian (GLM, GAM, mixed normal, etc.) multivariate models, the present work gives a unified, explicit theory for the general asymptotic (normal) distribution of maximum likelihood estimators (MLE). MLE can be complex and computationally hard, but we show a strong asymptotic equivalence between MLE and a relatively simple minimum (Mahalanobis) distance estimator. The latter method yields particularly simple tests of rank, and we describe its asymptotic behavior in detail. We also examine the method's performance in simulation and via analytical and empirical examples.
The prenatal setting/programming of human postnatal growth is an under-researched area even though the effects of prenatal programming on the human body and its functions are considerable. The aim of ...this association study was to determine whether there is a link between postnatal growth in adolescence and dermatoglyphics as putative markers of prenatal sex differentiation. The sample is represented by data acquired in three subsequent years of a semi-longitudinal study; the total sample included 166 participants. 83 participants were children aged 0-18 years (43 boys). The adults were represented by their mothers. A recently developed method based on Functional Principal Component Analysis was used for prediction of individual adolescent growth milestones, including age at peak velocity, which were correlated with dermatoglyphic between-finger ridge count contrasts of the studied children and their mothers. We found that childrens own dermatoglyphic traits correlated more with growth milestones in boys than in girls, while mothers' dermatoglyphic traits correlated more with girls' growth milestones. The strongest correlations were often provided by contrasts calculated from the ridge count of the 2nd or 4th finger, which appear to be most closely related to prenatal sex determination. Despite the limitations of this pilot study, it is the first study of the association between dermatoglyphics and postnatal growth in adolescence. When considered in a biological context, the results provide a promising basis for searching for prenatal origins of variation in some aspects (timing, velocity) of postnatal growth that can be further tested and elaborated in future independent studies.
Multispectral image compression Kaarna, A.; Zemcik, P.; Kalviainen, H. ...
Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170),
1998, Letnik:
2
Conference Proceeding
Image compression has been one of the mainstream research topics in image processing. The research usually focuses on compressing images that are visible to humans. Images are usually gray-level ...images or RGB color images. Advances in technology enable one to make the detailed processing of spectral color features in the images. Therefore, compression of images with many spectral color channels, called multispectral images, is required. Many methods used in traditional lossy image compression can be reused also in the compression of multispectral images. In this paper a new combination of clustering of colors, manipulating spectral color encoding and decoding for multispectral images is presented. The approach is based on extracting relevant color information. Furthermore, some quantitative quality measures for multispectral images are presented.
The presented system (Unicam) offers a complex state-of-the-art machine vision equipment and technology to provide automated video image vehicle detection devices dedicated for traffic monitoring ...applications. The system provides real time video image capturing, digital signal processing, compression, storage, and transmission over communication interfaces. It uses proprietary artificial intelligence algorithms and special image processing modules to achieve highly accurate vehicles detection. According to the users' needs, the system can be used for detection of red-light violations at road intersections, speed measurement, traffic data collection, video recording, or surveillance. Yet another possible application of the system is surveys based on license plate recognition for transportation engineers, stolen car searching, or toll-tag data collection. The system functionality has been improved by coupling camera sensors with specialized real-time processing units and adding networking capability. Implementation of video detection algorithms, hardware design units, and networking features are also discussed.
Particle rendering engine in DSP and FPGA Zemcik, P.; Herout, A.; Crha, L. ...
Proceedings. 11th IEEE International Conference and Workshop on the Engineering of Computer-Based Systems, 2004,
2004
Conference Proceeding
We present an algorithm for rendering 3D point-clouds, which exploits an FPGA chip coupled with a DSP processor on an experimental board. Point-clouds are sets of graphical data in 3D space, which ...seem to be more suitable for potentially many purposes than the most frequently, used triangle meshes. The actual experimental implementation, which verifies the concept and reports promising results, is also described.
Computing performance of today's graphics hardware grows fast as well as amount of rendered data. Modern graphics engines enable a possibility to use an arbitrary number of textures with arbitrary ...resolutions. On the other hand, high quality distributed 3D virtual environments can't exploit the computation power due to the limited network bandwidth. The problem mainly appears just in case the designers of such environments use high resolution textures. To overcome this streaming bottleneck an efficient prefetching scheme should be proposed. Instead of blind greedy scheduling policy we propose a scheme which exploits movement history of users to realize a look-ahead policy which enables the clients to retrieve potentially rendered data in advance. The prediction itself is established by Markov chains due to their ability to fast learning in conjunction with 2-state predictor which increases ability of the scheduling system to adapt to new habits of particular users.
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