A single-chip FPGA implementation of real-time adaptive background model

This paper demonstrates the use of a single-chip FPGA for the extraction of highly accurate background models in real-time. The models are based on 24-bit RGB values and 8-bit grayscale intensity values. Three background models are presented, all using a camcorder, single FPGA chip, four blocks of RAM and a display unit. The architectures have been implemented and tested using a Panasonic NVDS60B digital video camera connected to a Celoxica RC300 Prototyping Platform with a Xilinx Virtex II XC2v6000 FPGA and 4 banks of onboard RAM. The novel FPGA architecture presented has the advantages of minimizing latency and the movement of large datasets, by conducting time critical processes on BlockRAM. The systems operate at clock rates ranging from 57MHz to 65MHz and are capable of performing pre-processing functions like temporal low-pass filtering on standard frame size of 640X480 pixels at up to 210 frames per second

Computer Vision Techniques for Background Modeling in Urban Traffic Monitoring

Jose Manuel Milla, Sergio Luis Toral, Manuel Vargas and Federico Barrero (2010). Computer Vision Techniques for Background Modeling in Urban Traffic Monitoring, Urban Transport and Hybrid Vehicles, Seref Soylu (Ed.), ISBN: 978-953-307-100-8, InTech, DOI: 10.5772/10179. Available from: http://www.intechopen.com/books/urban-transport-and-hybrid-vehicles/computer-vision-techniques-for-background-modeling-in-urban-traffic-monitoringIn this chapter, several background modelling techniques have been described, analyzed and tested. In particular, different algorithms based on sigma-delta filter have been considered due to their suitability for embedded systems, where computational limitations affect a real-time implementation. A qualitative and a quantitative comparison have been performed among the different algorithms. Obtained results show that the sigma-delta algorithm with confidence measurement exhibits the best performance in terms of adaptation to particular specificities of urban traffic scenes and in terms of computational requirements. A prototype based on an ARM processor has been implemented to test the different versions of the sigma-delta algorithm and to illustrate several applications related to vehicle traffic monitoring and implementation details

Novel image processing algorithms and methods for improving their robustness and operational performance

Image processing algorithms have developed rapidly in recent years. Imaging functions are becoming more common in electronic devices, demanding better image quality, and more robust image capture in challenging conditions. Increasingly more complicated algorithms are being developed in order to achieve better signal to noise characteristics, more accurate colours, and wider dynamic range, in order to approach the human visual system performance levels. [Continues.

Reconstructing cosmic growth with kSZ observations in the era of Stage IV experiments

Future ground-based CMB experiments will generate competitive large-scale structure datasets by precisely characterizing CMB secondary anisotropies over a large fraction of the sky. We describe a method for constraining the growth rate of structure to sub-1% precision out to $z\approx 1$, using a combination of galaxy cluster peculiar velocities measured using the kinetic Sunyaev-Zel'dovich (kSZ) effect, and the velocity field reconstructed from galaxy redshift surveys. We consider only thermal SZ-selected cluster samples, which will consist of $\mathcal{O}(10^4-10^5)$ sources for Stage 3 and 4 CMB experiments respectively. Three different methods for separating the kSZ effect from the primary CMB are compared, including a novel blind "constrained realization" method that improves signal-to-noise by a factor of $\sim 2$ over a commonly-used aperture photometry technique. Measurements of the integrated tSZ $y$-parameter are used to break the kSZ velocity-optical depth degeneracy, and the effects of including CMB polarization and SZ profile uncertainties are also considered. A combination of future Stage 4 experiments should be able to measure the product of the growth and expansion rates, $\alpha\equiv f H$, to better than 1% in bins of $\Delta z = 0.1$ out to $z \approx 1$ -- competitive with contemporary redshift-space distortion constraints from galaxy surveys.Comment: 16 pages, 8 figure

Foreground detection of video through the integration of novel multiple detection algorithims

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityThe main outcomes of this research are the design of a foreground detection algorithm, which is more accurate and less time consuming than existing algorithms. By the term accuracy we mean an exact mask (which satisfies the respective ground truth value) of the foreground object(s). Motion detection being the prior component of foreground detection process can be achieved via pixel based and block based methods, both of which have their own merits and disadvantages. Pixel based methods are efficient in terms of accuracy but a time consuming process, so cannot be recommended for real time applications. On the other hand block based motion estimation has relatively less accuracy but consumes less time and is thus ideal for real-time applications. In the first proposed algorithm, block based motion estimation technique is opted for timely execution. To overcome the issue of accuracy another morphological based technique was adopted called opening-and-closing by reconstruction, which is a pixel based operation so produces higher accuracy and requires lesser time in execution. Morphological operation opening-and-closing by reconstruction finds the maxima and minima inside the foreground object(s). Thus this novel simultaneous process compensates for the lower accuracy of block based motion estimation. To verify the efficiency of this algorithm a complex video consisting of multiple colours, and fast and slow motions at various places was selected. Based on 11 different performance measures the proposed algorithm achieved an average accuracy of more than 24.73% than four of the well-established algorithms. Background subtraction, being the most cited algorithm for foreground detection, encounters the major problem of proper threshold value at run time. For effective value of the threshold at run time in background subtraction algorithm, the primary component of the foreground detection process, motion is used, in this next proposed algorithm. For the said purpose the smooth histogram peaks and valley of the motion were analyzed, which reflects the high and slow motion areas of the moving object(s) in the given frame and generates the threshold value at run time by exploiting the values of peaks and valley. This proposed algorithm was tested using four recommended video sequences including indoor and outdoor shoots, and were compared with five high ranked algorithms. Based on the values of standard performance measures, the proposed algorithm achieved an average of more than 12.30% higher accuracy results

AURORA:autonomous real-time on-board video analytics

In this paper, we describe the design and implementation of a small light weight, low-cost and power-efficient payload system for the use in unmanned aerial vehicles (UAVs). The primary application of the payload system is that of performing real-time autonomous objects detection and tracking in the videos taken from a UAV camera. The implemented objects detection and tracking algorithms utilise Recursive Density Estimation (RDE) and Evolving Local Means (ELM) clustering to perform detection and tracking moving objects. Furthermore, experiments are presented which demonstrate that the introduced system is able to detect by on-board processing any moving objects from a UAV and start tracking them in real-time while at the same time sending important data only to a control station located on the ground

COrE (Cosmic Origins Explorer) A White Paper

COrE (Cosmic Origins Explorer) is a fourth-generation full-sky, microwave-band satellite recently proposed to ESA within Cosmic Vision 2015-2025. COrE will provide maps of the microwave sky in polarization and temperature in 15 frequency bands, ranging from 45 GHz to 795 GHz, with an angular resolution ranging from 23 arcmin (45 GHz) and 1.3 arcmin (795 GHz) and sensitivities roughly 10 to 30 times better than PLANCK (depending on the frequency channel). The COrE mission will lead to breakthrough science in a wide range of areas, ranging from primordial cosmology to galactic and extragalactic science. COrE is designed to detect the primordial gravitational waves generated during the epoch of cosmic inflation at more than $3\sigma$ for $r=(T/S)>=10^{-3}$. It will also measure the CMB gravitational lensing deflection power spectrum to the cosmic variance limit on all linear scales, allowing us to probe absolute neutrino masses better than laboratory experiments and down to plausible values suggested by the neutrino oscillation data. COrE will also search for primordial non-Gaussianity with significant improvements over Planck in its ability to constrain the shape (and amplitude) of non-Gaussianity. In the areas of galactic and extragalactic science, in its highest frequency channels COrE will provide maps of the galactic polarized dust emission allowing us to map the galactic magnetic field in areas of diffuse emission not otherwise accessible to probe the initial conditions for star formation. COrE will also map the galactic synchrotron emission thirty times better than PLANCK. This White Paper reviews the COrE science program, our simulations on foreground subtraction, and the proposed instrumental configuration.Comment: 90 pages Latex 15 figures (revised 28 April 2011, references added, minor errors corrected