1150626
A Flexible New Technique for Camera Calibration
We propose a flexible technique to easily calibrate a camera. It only requires the camera to observe a planar pattern shown at a few (at least two) different orientations. Either the camera or the planar pattern can be freely moved. The motion need not be known. Radial lens distortion is modeled. The proposed procedure consists of a closed-form solution, followed by a nonlinear refinement based on the maximum likelihood criterion. Both computer simulation and real data have been used to test the proposed technique and very good results have been obtained. Compared with classical techniques which use expensive equipment such as two or three orthogonal planes, the proposed technique is easy to use and flexible. It advances 3D computer vision one more step from laboratory environments to real world use.
206417245
Estimation of Displacements from Two 3-D Frames Obtained From Stereo
A method for estimating 3D displacements from two stereo frames is presented. It is based on the hypothesize-and-verify paradigm used to match 3D line segments between the two frames. In order to reduce the complexity of the method, an assumption is made that objects are rigid. The formulate a set of complete rigidity constraints for 3D line segments and integrate the uncertainty of measurements in this formation. The hypothesize-and-verify stages of the method use an extended Kalman filter to produce estimates of the displacements and of their uncertainty. The algorithm is shown to work on indoor and natural scenes. It is also shown to be easily extended to the case in which several mobile objects are present. The method is quite robust, fast, and has been thoroughly tested on hundreds of real stereo frames. >
29303828
Parameter estimation techniques: a tutorial with application to conic fitting
Almost all problems in computer vision are related in one form or another to the problem of estimating parameters from noisy data. In this tutorial, we present what is probably the most commonly used techniques for parameter estimation. These include linear least-squares (pseudo-inverse and eigen analysis); orthogonal least-squares; gradient-weighted least-squares; bias-corrected renormalization; Kalman filtering; and robust techniques (clustering, regression diagnostics, M-estimators, least median of squares). Particular attention has been devoted to discussions about the choice of appropriate minimization criteria and the robustness of the different techniques. Their application to conic fitting is described.
1727845
Estimating the Fundamental Matrix by Transforming Image Points in Projective Space
This paper proposes a novel technique for estimating the fundamental matrix by transforming the image points in projective space. We therefore only need to perform nonlinear optimization with one parameterization of the fundamental matrix, rather than considering 36 distinct parameterizations as in previous work. We also show how to preserve the characteristics of the data noise model from the original image space.
16733151
A unified fuzzy feature indexing scheme for region based online image querying
We describe a novel indexing and retrieval methodology integrating color, texture and shape information for content-based image retrieval in online image databases. This methodology, called PicSearcher, applies unsupervised image segmentation to partition an image into a set of regions, then fuzzy color histogram as well as fuzzy texture and shape properties of each region is calculated to be part of their signatures. The fuzzification procedures resolve the recognition uncertainty stemming from color quantization and human perception of colors. At the same time, this unified fuzzy scheme incorporates the segmentation-related uncertainties into the retrieval algorithm. Then an adaptive and effective measure for the overall similarity between images is developed by integrating properties of all the regions in the image. An implemented prototype system of PicSearcher has demonstrated a promising retrieval performance for an online test database containing 10,000 general-purpose color images, as compared with its peer systems in the literature.
29068146
PseudoPipe: an automated pseudogene identification pipeline
MOTIVATION
Mammalian genomes contain many 'genomic fossils' i.e. pseudogenes. These are disabled copies of functional genes that have been retained in the genome by gene duplication or retrotransposition events. Pseudogenes are important resources in understanding the evolutionary history of genes and genomes.


RESULTS
We have developed a homology-based computational pipeline ('PseudoPipe') that can search a mammalian genome and identify pseudogene sequences in a comprehensive and consistent manner. The key steps in the pipeline involve using BLAST to rapidly cross-reference potential "parent" proteins against the intergenic regions of the genome and then processing the resulting "raw hits" -- i.e. eliminating redundant ones, clustering together neighbors, and associating and aligning clusters with a unique parent. Finally, pseudogenes are classified based on a combination of criteria including homology, intron-exon structure, and existence of stop codons and frameshifts.
9407873
Linear combination representation for outlier detection in motion tracking
In this paper we show that Ullman and Basri's linear combination (LC) representation, which was originally proposed for alignment-based object recognition, can be used for outlier detection in motion tracking with an affine camera. For this task LC can be realized either on image frames or feature trajectories, and therefore two methods are developed which we call linear combination of frames and linear combination of trajectories. For robust estimation of the linear combination coefficients, the support vector regression (SVR) algorithm is used and compared with the RANSAC method. SVR based on quadratic programming optimization can efficiently deal with more than 50 percent outliers and delivers more consistent results than RANSAC in our experiments. The linear combination representation can use SVR in a straightforward manner while previous factorization-based or subspace separation methods cannot. Experimental results are presented using real video sequences to demonstrate the effectiveness of our LC+SVR approaches, including a quantitative comparison of SVR and RANSAC.
5573915
Head pose determination from one image using a generic model
We present a new method for determining the pose of a human head from its 2D image. It does not use any artificial markers put on a face. The basic idea is to use a generic model of a human head, which accounts for variation in shape and facial expression. Particularly, a set of 3D curves are used to model the contours of eyes, lips and eyebrows. A technique called iterative closest curve matching (ICC) is proposed, which aims at recovering the pose by iteratively minimizing the distances between the projected model curves and their closest image curves. Because curves contain richer information (such as curvature and length) than points, ICC is both more robust and more efficient than the well-known iterative closest point matching techniques (ICP). Furthermore, the image can be taken by a camera with unknown internal parameters, which can be recovered by our technique thanks to the 3D model. Preliminary experiments show that the proposed technique is promising and that an accurate pose estimate can be obtained from just one image with a generic head model.
1313086
Image-based surface detail transfer
Changing an object's appearance by adding geometric details is desirable in many real-world applications. Bump mapping has acted as an alternative to adding geometrical details, to an otherwise smooth object. But constructing visually interesting bump maps requires practice and artistic skills. Computer vision techniques have helped for modeling real-world objects and their surface details. In our approach, for cases where we only want to transfer geometrical details from one object to another, we might not need to explicitly compute 3D structures. In particular, our novel technique captures the geometrical details of an object from a single image in a way that is independent of the object's reflectance property. We can then transfer geometrical details to another surface, producing the appearance of a new surface with added geometrical details while preserving the object's reflectance property. Our method's advantages are that it's simple to implement, requires only a single image for each object, and produces effective results.