Computer Vision Source Code. Research Code A rational methodology for lossy compression. REWIC is a software- based implementation of a a rational system for progressive transmission which, in absence of a priori knowledge about regions of interest, choose at any truncation time among alternative trees for further transmission.
To circumvent the lack of knowledge of what distortion measure is more suitable for optimization of the trade- off between image fidelity and coding rate, this coder shall introduce a novel mathematical methodology for rate control by organizing the progressive transmission in accordance with coherence constraints for avoiding forms of behavioral inconsistency. A set of postulates is provided for specifying the ways in which preferences need to be made precise and fit together if illogical forms of behavior are to be avoided. We show that the rational choice for transmission at truncation time t is to select bit streams which have the maximum expected increase in utility per coding bit, where ``rational'' must be understood in the sense that it cannot lead the transmission system into forms of behavioral inconsistency. This method is then used within a progressive transmission scheme to produce a new compression method called rational embedded wavelet image coding (REWIC).
Free modula-2 resources. Bash Scripts for Vim. The following are simple and short bash scripts which I use to save time when working with GNU Modula-2 and Vim. FILExt.com is the file extension source. Here you'll find a collection of file extensions; many linked to the programs that created the files. This is the FILExt home.
Fdez- Valdivia / Computer Vision Group. University of Granada. Several results and models are also given. Paul Rosin, Svetha Venkatesh / Cardiff University / Cardiff University) Belief Propagation for Early Vision. Fast algorithms for MRF based stereo and image restoration.
I want to synchronise two folders in real time under Windows 7. Basically, I want to monitor a folder and synchronise each change (new files, changed files, deleted. I run a (remotely hosted) virtual Server with Windows 2008 Server for a client. Initially, it had 10 GB of space. During the course of a few weeks - during which. Supported Formats. Currently pstoedit can generate the following major formats. I'm in a corporate Windows environment, which has deployed its own WSUS server. The thing is, it seems to hardly ever be updated. This means I don't get the latest.
It is also an open architecture so that one can import their own C/C++ functions. It could be easily extended and used in 3. D video conferencing applications. The effectiveness of a coding method can be improved through a space- varying filterbank tree representation of the image, and this property can be conveniently exploited using appropriate bit allocation strategies among the spatial segments of the image. In CORAL we examine the conditions for achieving a rational agreement on the distribution problem by stating axioms that its solution must obey in absence of a priori knowledge about regions of interest. Firstly, a measure of benefit avoiding certain forms of behavioral inconsistency is to be assigned to each possible bit allocation in such a way that each region's preference may be inferred between any two bit allocations from their respective benefits. Secondly, individual regions are to agree on an allocation of bits which is then to be brought about by a joint strategy, but, under what conditions is their agreement rational?
CORAL propose a characterization of rational agreement whose solution is an application of a general procedure for cooperative action where each may benefit only on terms which permit proportionately equal benefits to others. Experimental results are given to evaluate the performance of the strategy of COllective Rationality for the ALlocation of bits (CORAL), based upon a validated predictor for visual distinctness from digital imagery. Fdez- Valdivia / Computer Vision Group. University of Granada.
Spain) Convex grouping code. Robustly locates salient convex collections of line segments in an image. It let you control the camera, plus save, FTP, stream and display live video. It works by first detecting remarkable points in both images and then finding the best possible match between the two sets of points.
The preview application demonstrates a simple integration of Intel's Open. CV library and the MPEG- 4 AVC reference software. Gandalf has been used to develop the . Mo. Key performs automatic inpainting of moving objects over an image sequence, and can also be used to compute an accurate alpha matte or outline of an object. Gandalf currently contains four packages: 1) Common package of simple structures and routines used by the other packages, such as memory allocation, linked lists and error handling; 2) Linear algebra package with a large number of routines for matrix and vector manipulations; 3) Image package defining a general purpose image structure and low- level image manipulation routines; 4) Vision package containing a number of standard image processing, computer vision and numerical routines.
The major design features of Gandalf are: (i) Efficient use of memory through dynamically reconfigurable structures; (ii) Emphasis on support of numerical algorithms, especially optimisation; (iii) A very flexible and efficient internal image representation, (iv) A comprehensive set of matrix/vector operations, incorporating implicit matrix transpose & inverse, and in- place computation where appropriate; Exploitation of the computational and compilation speed advantages of C over C++ in reducing the number of layers of abstraction over the raw data, an approach we believe is appropriate for simple objects such as matrices, vectors and images. The documentation for Gandalf comes in two parts. There is a La. Tex tutorial with examples available also in HTML (via Latex. Reference documentation for Gandalf has also been generated using Object. Outline. (by Philip Mc.
Lauchlan / Imagineer Software Ltd) General Image Rectification. Re- usable free C++ source code library for performing general image rectification Rectification is the process of simplifying the epipolar geometry by making epipolar lines in a pair of images co- incident and parallel to the x axis.
The code presented here is a free C++ library incl. The method used is general and so will work for ANY valid epipolar geometry. The method also has the advantage over other methods of attempting to minimise image distortion caused by rectification and ensuring that disparities will be roughly centred on 0 pixels. Matlab implementation is available for both UNIX and Windows. Prince / Image Analysis and Communications Laboratory / Johns Hopkins University) GREYCstoration : A fast PDE- based algorithm for image restoration. Several examples are provided, and the executable can be downloaded for Windows and Unix. The code follows Rabiner and Juang notation.
Open Source, FREE for academic AND commercial use. Assembly language optimized on Intel's processor line. Bradski , Valery Cherepennikov , Michael Chu , Boris Chudinovich , Prof. Trevor , Bob Davies , Prof. James Davis , Victor Eroukhimov , Prof. Irfan Essa , Radek Grzeszczuk , Mark Holler , Prof.
Jitendra Malik , Sergey Molinov , Valery Mosyagin , Ara Nefian , Sergey Oblomov , Prof. Pietro Perona , Vadim Pisarevsky, Alexander Pleskov, Chuck Richards, Prof. Stan Scarloff, Stewart Taylor, Prof. Carlo Tomasi / Visual Interactivity Lab / Intel Corporation) KLT. An implementation of the Kanade- Lucas- Tomasi feature tracker. The LTI- Lib is an object oriented library with algorithms and data structures frequently used in image processing and computer vision. It has been developed at the Chair of Technical Computer Science (Lehrstuhl fuer Technische Informatik) LTI at the Aachen University of Technology, as part of many research projects in computer vision dealing with robotics, object recognition and sing language and gesture recognition.
The project provides useful example programs which run real time computer vision algorithms on single or parallel graphics processing units(GPU). The Open. VIDIA project implements computer vision algorithms on computer graphics hardware in real- time, using Open. GL and Cg. The project provides useful example programs which run real time computer vision algorithms on single or parallel graphics processing units(GPU). Open. VIDIA utilizes the computational power of the GPU to provide real- -time computer vision much faster than the CPU is capable of, and leaves the CPU free to conduct other tasks beyond vision. It relies on a two- pass algorithm. The output is more robust and informative as input for techniques such as snakes.
An automatic method for segmention of images of skin cancer and other pigmented lesions is implemented. This method first reduces a color image into an intensity image and approximately segments the image by intensity thresholding.
Then, it refines the segmentation using image edges. Double thresholding is used to focus on an image area where a lesion boundary potentially exists.
Image edges are then used to localize the boundary in that area. A closed elastic curve is fitted to the initial boundary and is locally shrunk or expanded to approximate edges in its neighborhood in the area of focus. Segmentation results from twenty randomly selected images show an average error that is about the same as that obtained by four experts manually segmenting the images. Jackowski, A. Goshtasby, C. Huntley / Intelligent Systems Laboratory / Wright State University) Sketch. Up. - A demo package for recognizing hand- drawn sketches through Size Functions. In this toolbox we have additionaly implemented our Jacobian matrix factorisation for a projective motion model (see paper: Real- time tracking and estimation of plane pose, Jos.
IEEE. Quebec, Canada, August 2. Buenaposada, Luis Baumela / Technical University of Madrid (Universidad Polit. The device uses a calibration object. Non- linear estimation of the parameters of a single camera. Non- linear estimation of the parameters of a stereo- rig from several positions of a calibration object.
D reconstruction and metrologic statistics. SUSAN is an acronym for Smallest Univalue Segment Assimilating Nucleus. The SUSAN algorithms cover image noise filtering, edge finding and corner finding. Target. Jr has been developed over the last 1. GE's Corporate R& D Center. Currently Target.
Jr is used by a number of vision research groups with emaphasis on geometric algorithms and object recognition. Target. Jr is written in C++ and organized into a number of libraries including: numerics; spatial objects; image; image processing; segmentation; computational geometry; 3- d modeling; and user interface. R& D, Oxford University, University of Leuven) Texture Synthesis and Analysis by Rupert Paget.