3D Shape Recovery of Smooth Surfaces: Dropping the Fixed-Viewpoint Assumption

We present a new method for recovering the 3D shape of a featureless smooth surface from three or more calibrated images illuminated by different light sources (three of them are independent). This method is unique in its ability to handle images taken from unconstrained perspective viewpoints and unconstrained illumination directions. The correspondence between such images is hard to compute and no other known method can handle this problem locally from a small number of images. Our method combines geometric and photometric information in order to recover dense correspondence between the images and accurately computes the 3D shape. Only a single pass starting at one point and local computation are used. This is in contrast to methods that use the occluding contours recovered from many images to initialize and constrain an optimization process. The output of our method can be used to initialize such processes. In the special case of fixed viewpoint, the proposed method becomes a new perspective photometric stereo algorithm. Nevertheless, the introduction of the multiview setup, self-occlusions, and regions close to the occluding boundaries are better handled, and the method is more robust to noise than photometric stereo. Experimental results are presented for simulated and real images.     

Reliable and efficient landmark-based localization for mobile robots

This paper describes an efficient and robust localization system for indoor mobile robots and AGVs. The system utilizes a sensor that measures bearings to artificial landmarks, and an efficient triangulation method. We present a calibration method for the system components and overcome typical problems for sensors of the mentioned type, which are localization in motion and incorrect identification of landmarks. The resulting localization system was tested on a mobile robot. It consumes less than 4% of a Pentium4 3.2 GHz processing power while providing an accurate and reliable localization result every 0.5 s. The system was successfully incorporated within a real mobile robot system which performs many other computational tasks in parallel.     

A geometric interpretation of weak-perspective motion

We present a geometric interpretation of the problem of motion recovery from three weak-perspective images. Our interpretation is based on reducing the problem of estimating the motion to a problem of finding triangles on a sphere whose angles are known. Using this geometric interpretation, a simple method to completely recover the motion parameters using three images is developed. The results of running the algorithm on real images are presented. In addition, we describe which of the various motion parameters can be recovered already from two images     

Visual Homing: Surfing on the Epipoles

We introduce a novel method for visual homing. Using this method a robot can be sent to desired positions and orientations in 3D space specified by single images taken from these positions. Our method is based on recovering the epipolar geometry relating the current image taken by the robot and the target image. Using the epipolar geometry, most of the parameters which specify the differences in position and orientation of the camera between the two images are recovered. However, since not all of the parameters can be recovered from two images, we have developed specific methods to bypass these missing parameters and resolve the ambiguities that exist. We present two homing algorithms for two standard projection models, weak and full perspective.Our method determines the path of the robot on-line, the starting position of the robot is relatively not constrained, and a 3D model of the environment is not required. The method is almost entirely memoryless, in the sense that at every step the path to the target position is determined independently of the previous path taken by the robot. Because of this property the robot may be able, while moving toward the target, to perform auxiliary tasks or to avoid obstacles, without this impairing its ability to eventually reach the target position. We have performed simulations and real experiments which demonstrate the robustness of the method and that the algorithms always converge to the target pose.     

Robust real-time unusual event detection using multiple fixed-location monitors

We present a novel algorithm for detection of certain types of unusual events. The algorithm is based on multiple local monitors which collect low-level statistics. Each local monitor produces an alert if its current measurement is unusual, and these alerts are integrated to a final decision regarding the existence of an unusual event. Our algorithm satisfies a set of requirements that are critical for successful deployment of any large-scale surveillance system. In particular it requires a minimal setup (taking only a few minutes) and is fully automatic afterwards. Since it is not based on objects' tracks, it is robust and works well in crowded scenes where tracking-based algorithms are likely to fail. The algorithm is effective as soon as sufficient low-level observations representing the routine activity have been collected, which usually happens after a few minutes. Our algorithm runs in realtime. It was tested on a variety of real-life crowded scenes. A ground-truth was extracted for these scenes, with respect to which detection and false-alarm rates are reported.     

Prominent Field for Shape Processing and Analysis of?Archaeological Artifacts

Archaeological artifacts are an essential element of archaeological research. They provide evidence of the past and enable archaeologists to obtain qualified conclusion. Nowadays, many artifacts are scanned by 3D scanners. While convenient in many aspects, the 3D representation is often unsuitable for further analysis, due to flaws in the scanning process or defects in the original artifacts. We propose a new approach for automatic processing of scanned artifacts. It is based on the definition of a new direction field on surfaces (a normalized vector field), termed the prominent field. The prominent field is oriented with respect to the prominent feature curves of the surface. We demonstrate the applicability of the prominent field in two applications. The first is surface enhancement of archaeological artifacts, which helps enhance eroded features and remove scanning noise. The second is artificial coloring that can replace manual artifact illustration in archaeological reports.     

Can providing feedback on driving behavior and training on parental vigilant care affect male teen drivers and their parents?

This study focuses on investigating the driving behavior of young novice male drivers during the first year of driving (three months of accompanied driving and the following nine months of solo driving). The study's objective is to examine the potential of various feedback forms on driving to affect young drivers’ behavior and to mitigate the transition from accompanied to solo driving. The study examines also the utility of providing parents with guidance on how to exercise vigilant care regarding their teens’ driving. Driving behavior was evaluated using data collected by In-Vehicle Data Recorders (IVDR), which document events of extreme g-forces measured in the vehicles.     

Guided Sampling via Weak Motion Models and Outlier Sample Generation for Epipolar Geometry Estimation

The problem of automatic robust estimation of the epipolar geometry in cases where the correspondences are contaminated with a high percentage of outliers is addressed. This situation often occurs when the images have undergone a significant deformation, either due to large rotation or wide baseline of the cameras. An accelerated algorithm for the identification of the false matches between the views is presented. The algorithm generates a set of weak motion models (WMMs). Each WMM roughly approximates the motion of correspondences from one image to the other. The algorithm represents the distribution of the median of the geometric distances of a correspondence to the WMMs as a mixture model of outlier correspondences and inlier correspondences. The algorithm generates a sample of outlier correspondences from the data. This sample is used to estimate the outlier rate and to estimate the outlier pdf. Using these two pdfs the probability that each correspondence is an inlier is estimated. These probabilities enable guided sampling. In the RANSAC process this guided sampling accelerates the search process. The resulting algorithm when tested on real images achieves a speedup of between one or two orders of magnitude. This work was supported partly by grant 01-99-08430 of the Israeli Space Agency through the Ministry of Science Culture and Sports of Israel.     

Recognizing 3D Objects Using Tactile Sensing and Curve Invariants

A general paradigm for recognizing 3D objects is offered, and applied to some geometric primitives (spheres, cylinders, cones, and tori). The assumption is that a curve on the surface, or a pair of intersecting curves, was measured with high accuracy (for instance, by a sensory robot). Differential invariants of the curve(s) are then used to recognize the surface. The motivation is twofold: the output of some devices is not surface range data, but such curves. Also, a considerable speedup is obtained by using curve data, as opposed to surface data which usually contains a much higher number of points.We survey global, algebraic methods for recognizing surfaces, and point out their limitations. After introducing some notions from differential geometry and elimination theory, the differential and semi-differential approaches to the problem are described, and novel invariants which are based on the curve's curvature and torsion are derived.     

ROR: rejection of outliers by rotations

We address the problem of rejecting false matches of points between two perspective views. The two views are taken from two arbitrary, unknown positions and orientations. We present an algorithm for identification of the false matches between the views. The algorithm exploits the possibility of rotating one of the images to achieve some common behavior of the correct matches. Those matches that deviate from this common behavior turn out to be false matches. Our algorithm does not, in any way, use the image characteristics of the matched features. In particular, it avoids problems that cause the false matches in the first place. The algorithm works even in cases where the percentage of false matches is as high as 85 percent. The algorithm may be run as a post-processing step on output from any point matching algorithm. Use of the algorithm may significantly improve the ratio of correct matches to incorrect matches. We present the algorithm, identify the conditions under which it works, and present results of the test.