## Daniilidis, Kostas

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Publication View-Independent Scene Acquisition for Tele-Presence(2000-10-05) Mulligan, Jane; Daniilidis, KostasTele-immersion is a new medium that enables a user to share a virtual space with remote participants. The user is immersed in a rendered 3D-world that is transmitted from a remote site. To acquire this 3D description we apply bi- and trinocular stereo techniques. The challenge is to compute dense stereo range data at high frame rates, since participants cannot easily communicate if the processing cycle or network latencies are long. Moreover, new views of the received 3D-world must be as accurate as possible. We address both issues of speed and accuracy and we propose a method for combining motion and stereo in order to increase speed and robustness.Publication Structure and Motion From Uncalibrated Catadioptric Views(2001-05-25) Geyer, Christopher; Daniilidis, KostasIn this paper we present a new algorithm for structure from motion from point correspondences in images taken from uncalibrated catadioptric cameras with parabolic mirrors. We assume that the unknown intrinsic parameters are three: the combined focal length of the mirror and lens and the intersection of the optical axis with the image. We introduce a new representation for images of points and lines in catadioptric images which we call the circle space. This circle space includes imaginary circles, one of which is the image of the absolute conic. We formulate the epipolar constraint in this space and establish a new 4x4 catadioptric fundamental matrix. We show that the image of the absolute conic belongs to the kernel of this matrix. This enables us to prove that Euclidean reconstruction is feasible from two views with constant parameters and from three views with varying parameters. In both cases, it is one less than the number of views necessary with perspective cameras.Publication Compression of Stereo Disparity Streams Using Wavelets and Optical Flow(2001-01-01) BÃ¼low, Thomas; Mulligan, Jane; Bonnafos, Geraud de; Chibane, Alexandre; Daniilidis, KostasRecent advances in computing have enabled fast reconstructions of dynamic scenes from multiple images. However, the efficient coding of changing 3D-data has hardly been addressed. Progressive geometric compression and streaming are based on static data sets which are mostly artificial or obtained from accurate range sensors. In this paper, we present a system for efficient coding of 3D-data which are given in forms of 2 + 1/2 disparity maps. Disparity maps are spatially coded using wavelets and temporally predicted by computing flow. The resulted representation of a 3D-stream consists then of spatial wavelet coefficients, optical flow vectors, and disparity differences between predicted and incoming image. The approach has also very useful by-products: disparity predictions can significantly reduce the disparity search range and if appropriately modeled increase the accuracy of depth estimation.Publication Image Registration Using Mutual Information(2000-01-01) Egnal, Geoffrey; Daniilidis, KostasAlmost all imaging systems require some form of registration. A few examples are aligning medical images for diagnosis, matching stereo images to recover shape, and comparing facial images in a database to recognize people. Given the difficulty of registering images taken at different times, using different sensors, from different positions, registration algorithms come in different shapes and sizes. Recently, a new type of solution to the registration problem has emerged, based on information theory. In particular, the mutual information similarity metric has been used to register multi-modal medical images. Mutual information compares the statistical dependence between the two images. Unlike many other registration techniques, mutual information makes few a priori assumptions about the surface properties of the object or the imaging process, making it adaptible to changes in lighting and changes between sensors. The method can be applied to larger dimensional registration and many other imaging situations. In this report, we compare two approaches taken towards the implementation of rigid 2D mutual information image registration. We look further at algorithm speedup and noise reduction efforts. A full background is provided.Publication Robust Invariants From Functionally Constrained Motion(1998-07-01) Hicks, Andrew R.; Daniilidis, Kostas; Bajcsy, Ruzena; Pettey, DavidWe address in the problem of control-based recovery of robot pose and the environmental lay-out. Panoramic sensors provide us with an 1D projection of characteristic features of a 2D operation map. Trajectories of these projections contain the information about the position of a priori unknown landmarks in the environment. We introduce here the notion of spatiotemporal signatures of projection trajectories. These signatures are global measures, like area, characterized by considerably higher robustness with respect to noise and outliers than the commonly applied point correspondence. By modeling the 2D motion plane as the complex plane we show that by means of complex analysis our method can be embedded in the well-known affine reconstruction paradigm.Publication VC-Dimension of Exterior Visibility of Polyhedra(2001-01-01) Kannan, Sampath; Isler, Volkan; Daniilidis, KostasIn this paper, we address the problem of finding the minimal number of viewpoints outside a polyhedron in two or three dimensions such that every point on the exterior of the polyhedron is visible from at least one of the chosen viewpoints. This problem which we call the minimum fortress guard problem (MFGP) is the optimization version of a variant of the art-gallery problem (sometimes called the fortress problem with point guards) and has practical importance in surveillance and image-based rendering. Solutions in the vision and graphics literature are based on image quality constraints and are not concerned with the number of viewpoints needed. The corresponding question for art galleries (minimum number of viewpoints in the interior of a polygon to see the interior of the polygon) which we call the minimum art-gallery guard problem (MAGP) has been shown to be NP-complete. A simple reduction from this problem shows the NP-completeness of MFGP. Instead of relying on heuristic searches, we address the approximability of the camera placement problem. It is well known (and easy to see) that this problem can be cast as a hitting set problem. While the approximability of generic instances of the hitting set problem is well understood, BrÃ¶nnimann and Goodrich[3] presented improved approximation algorithms for the problem in the case that the input instances have bounded Vapnik-Chervonenkis (VC) dimension. In this paper we explore the VC-dimension of set systems associated with the camera placement problem described above. We show a constant bound for the VC dimension in the two dimensional case but a tight logarithmic bound in the three dimensional case. In the two dimensional case we are also able to present an algorithm that uses at most one more viewpoint than the optimal in the case that the viewpoints are restricted to be on a circumscribing circle - a restriction that is justified in practice.Publication Motion Estimation Using a Spherical Camera(2004-01-01) Makadia, Ameesh A; Daniilidis, KostasRobotic navigation algorithms increasingly make use of the panoramic field of view provided by omnidirectional images to assist with localization tasks. Since the images taken by a particular class of omnidirectional sensors can be mapped to the sphere, the problem of attitude estimation arising from 3D motions of the camera can be treated as a problem of estimating the camera motion between spherical images. This problem has traditionally been solved by tracking points or features between images. However, there are many natural scenes where the features cannot be tracked with confidence. We present an algorithm that uses image features to estimate ego-motion without explicitly searching for correspondences. We formulate the problem as a correlation of functions defined on the product of spheres S2 Ã— S2 which are acted upon by elements of the direct product group SO(3) Ã— SO(3). We efficiently compute this correlation and obtain our solution using the spectral information of functions in S2 Ã— S2.Publication Fully Automatic Registration of 3D Point Clouds(2006-01-01) Makadia, Ameesh; Patterson, Alexander; Daniilidis, KostasWe propose a novel technique for the registration of 3D point clouds which makes very few assumptions: we avoid any manual rough alignment or the use of landmarks, displacement can be arbitrarily large, and the two point sets can have very little overlap. Crude alignment is achieved by estimation of the 3D-rotation from two Extended Gaussian Images even when the data sets inducing them have partial overlap. The technique is based on the correlation of the two EGIs in the Fourier domain and makes use of the spherical and rotational harmonic transforms. For pairs with low overlap which fail a critical verification step, the rotational alignment can be obtained by the alignment of constellation images generated from the EGIs. Rotationally aligned sets are matched by correlation using the Fourier transform of volumetric functions. A fine alignment is acquired in the final step by running Iterative Closest Points with just few iterations.Publication Approximate Orientation Steerability Based on Angular Gaussians(2001-02-01) Yu, Weichan; Daniilidis, Kostas; Sommer, GeraldJunctions are significant features in images with intensity variation that exhibits multiple orientations. This makes the detection and characterization of junctions a challenging problem. The characterization of junctions would ideally be given by the response of a filter at every orientation. This can be achieved by the principle of steerability that enables the decomposition of a filter into a linear combination of basis functions. However, current steerability approaches suffer from the consequences of the uncertainty principle: In order to achieve high resolution in orientation they need a large number of basis filters increasing, thus, the computational complexity. Furthermore, these functions have usually a wide support which only accentuates the computational burden. In this paper we propose a novel alternative to current steerability approaches. It is based on utilizing a set of polar separable filters with small support to sample orientation information. The orientation signature is then obtained by interpolating orientation samples using Gaussian functions with small support. Compared with current steerability techniques our approach achieves a higher orientation resolution with a lower complexity. In addition, we build a polar pyramid to characterize junctions of arbitrary inherent orientation scales.Publication Trinocular Stereo: A Real-Time Algorithm and its Evaluation(2002-04-01) Mulligan, Jane; Isler, Volkan; Daniilidis, KostasIn telepresence applications each user is immersed in a rendered 3D-world composed from representations transmitted from remote sites. The challenge is to compute dense range data at high frame rates, since participants cannot easily communicate if the processing cycle or network latencies are long. Moreover, errors in new stereoscopic views of the remote 3D-world should be hardly perceptible. To achieve the required speed and accuracy, we use trinocular stereo, a matching algorithm based on the sum of modified normalized cross-correlations, and subpixel disparity interpolation. To increase speed we use Intel IPL functions in the pre-processing steps of background subtraction and image rectification as well as a four-processor parallelization. To evaluate our system we have developed a testbed which provides a set of registered dense "ground-truth" laser data and image data from multiple views.