nils-herrmann/clean_scirepeval huggingface dataset:
A potential field approach to path planning

A path-planning algorithm for the classical mover's problem in three dimensions using a potential field representation of obstacles is presented. A potential function similar to the electrostatic potential is assigned to each obstacle, and the topological structure of the free space is derived in the form of minimum potential valleys. Path planning is done at two levels. First, a global planner selects a robot's path from the minimum potential valleys and its orientations along the path that minimize a heuristic estimate of the path length and the chance of collision. Then, a local planner modifies the path and orientations to derive the final collision-free path and orientations. If the local planner fails, a new path and orientations are selected by the global planner and subsequently examined by the local planner. This process is continued until a solution is found or there are no paths left to be examined. The algorithm solves a much wider class of problems than other heuristic algorithms and at the same time runs much faster than exact algorithms (typically 5 to 30 min on a Sun 3/260).
Generalized Pupil-centric Imaging and Analytical Calibration for a Non-frontal Camera

We consider the problem of calibrating a small field of view central perspective non-frontal camera whose lens and sensor planes may not be parallel to each other. This can be due to manufacturing defects or intentional tilting. Thus, as such all cameras can be modeled as being non-frontal with varying degrees. There are two approaches to model non- frontal cameras. The first one based on rotation parameterization of sensor non-frontalness/tilt increases the number of calibration parameters, thus requiring heuristics to initialize a few calibration parameters for the final non-linear optimization step. Additionally, for this parameterization, while it has been shown that pupil-centric imaging model leads to more accurate rotation estimates than a thin-lens imaging model, it has only been developed for a single axis lens-sensor tilt. But, in real cameras we can have arbitrary tilt. The second approach based on decentering distortion modeling is approximate as it can only handle small tilts and cannot explicitly estimate the sensor tilt. In this paper, we focus on rotation based non-frontal camera calibration and address the aforementioned problems of over-parameterization and inadequacy of existing pupil-centric imaging model. We first derive a generalized pupil-centric imaging model for arbitrary axis lens-sensor tilt. We then derive an analytical solution, in this setting, for a subset of calibration parameters including sensor rotation angles as a function of center of radial distortion (CoD). A radial alignment based constraint is then proposed to computationally estimate CoD leveraging on the proposed analytical solution. Our analytical technique also estimates pupil-centric parameters of entrance pupil location and optical focal length, which have typically been done optically. Given these analytical and computational calibration parameter estimates, we initialize the non-linear calibration optimization for a set of synthetic and real data captured from a non-frontal camera and show reduced pixel re-projection and undistortion errors compared to state of the art techniques in rotation and decentering based approaches to non-frontal camera calibration.
Active Aperture Control and Sensor Modulation for Flexible Imaging

In the paper, we describe an optical system which is capable of providing external access to both the sensor and the lens aperture (i.e., projection center) of a conventional camera. The proposed optical system is attached in front of the camera, and is the equivalent of adding externally accessible intermediate image plane and projection center. The system offers controls of the response of each pixel which could be used to realize many added imaging functions, such as high dynamic range imaging, image modulation, and optical computation. The ability to access the optical center could enable a wide variety of applications by simply allowing manipulation of the geometric properties of the optical center. For instance, panoramic imaging can be implemented by rotating a planar mirror about the camera axis; and small base-line stereo can be implemented by shifting the camera center. We have implemented a bench setup to demonstrate some of these functions. The experimental results are included.
Motion and Structure from Line Correspondences; Closed-Form Solution, Uniqueness, and Optimization

This work discusses estimating motion and structure parameters from line correspondences of a rigid scene. The authors present a closed-form solution to motion and structure parameters from line correspondences through three monocular perspective views. The algorithm makes use of redundancy in the data to improve the accuracy of the solutions. The uniqueness of the solution is established, and necessary and sufficient conditions for degenerate spatial line configurations are given. Optimization has been employed to further improve the accuracy of the estimates in the presence of noise. Simulations have shown that the errors of the optimized estimates are close to the theoretical lower error bound.
Performance Analysis of Stereo, Vergence, and Focus as Depth Cues for Active Vision

This paper compares the performances of the binocular cues of stereo and vergence, and the monocular cue of focus for range estimation using an active vision system. The performance of each cue is characterized in terms of sensitivity to errors in the imaging parameters. The effects of random, quantization errors are expressed in terms of the standard deviation of the resulting depth error. The effect of systematic, calibration errors on estimation using each cue is also studied. Performance characterization of each cue is utilized to evaluate the relative performance of the cues. Also discussed, based on such characterization, are ways to select a cue taking into account the computational and reliability aspects of the corresponding estimation process.
Sub-band Energy Constraints for Self-Similarity Based Super-resolution

In this paper, we propose a new self-similarity based single image super-resolution (SR) algorithm that is able to better synthesize fine textural details of the image. Conventional self-similarity based SR typically uses scaled down version(s) of the given image to first build a dictionary of low-resolution (LR) and high-resolution (HR) image patches, which is then used to predict the HR patches for each LR patch of the given image. However, metrics like pixel wise sum of squared differences (L2 distance) make it difficult to find matches for high frequency textured patches in the dictionary. Textural details are thus often smoothed out in the final image. In this paper, we propose a method to compensate for this loss of textural detail. Our algorithm uses the responses of a bank of orientation selective band pass filters to represent texture instead of the spatial variation of intensity values directly. Specifically, we use the energies contained in different sub-bands of an image patch to separate different types of details of a texture, which we then impose as additional priors on the patches of the super-resolved image. Our experiments show that for each patch, the low energy sub-bands (which correspond to fine textural details) get severely attenuated during conventional L2 distance based SR. We propose a method to learn this attenuation of sub-band energies in the patches, using scaled down version(s) of the given image itself (without requiring external training databases), and thus propose a way of compensating for the energy loss in these sub-bands. We demonstrate that as a consequence, our SR results appear richer in texture and closer to the ground truth as compared to several other state-of-the-art methods.
Efficient and Robust Specular Highlight Removal

A robust and effective specular highlight removal method is proposed in this paper. It is based on a key observation-the maximum fraction of the diffuse colour component in diffuse local patches in colour images changes smoothly. The specular pixels can thus be treated as noise in this case. This property allows the specular highlights to be removed in an image denoising fashion: an edge-preserving low-pass filter (e.g., the bilateral filter) can be used to smooth the maximum fraction of the colour components of the original image to remove the noise contributed by the specular pixels. Recent developments in fast bilateral filtering techniques enable the proposed method to run over 200× faster than state-of-the-art techniques on a standard CPU and differentiates it from previous work.
A generative focus measure with application to omnifocus imaging

Given a stack of registered images acquired using a range of focus settings (focal stack images), we propose a new focus measure to identify the most focused image. Although, most of the paper is concerned with the new focus measure, for evaluation purposes, we will present it in the context of an application to generating omnifocus images. An omnifocus image is the composite image in which each pixel is selected form the frame in the stack in which it appears to be in best focus. Conventional focus measures usually maximize some measure of image gradient in a window. They tend to fail when one of the edges of the window lies near the boundary of an intensity edge, or the pixel is near other complex edge patterns. This leads to the misidentification of the focused frame and formation of artifacts in omnifocused image. Our proposed measure does not attempt to identify the focused frame by calculating the degree of defocus, like the gradient based methods. Rather, it hypothesizes that a specific frame is in focus and then validates or rejects this hypothesis by recreating the defocused frames in the vicinity, and comparing them with the observed de-focused frames. This forward generative process leads to correct focus frame selection in regions where typical measures fail. This is because the conventional measures try to identify the focused frame from its distorted version which is the result of a complex convolution process. This involves a backward estimation for a many-to-one transformation. On the other hand, the generation of defocused frames from a hypothesized focused frame is more accurate since it involves applying an operator in the forward direction. We analytically show that under ideal imaging conditions, the proposed focus measure is unimodal in nature. This makes the search for the best focused image unambiguous. We evaluate our focus measure by generating omnifocus images from real focal stack images, and show that it performs better than all the existing focus measures.
Analysis of Ramp Discontinuity Model for Multiscale Image Segmentation

This paper presents an algorithm for multiscale image segmentation. Towards this, it proposes a new region model, that of a homogenous region surrounded by ramp discontinuities (a scenario usually encountered in real images). This paper presents the analysis of this model, leading to a robust algorithm for detection of ramp discontinuities in the image, and finally segmentation of the image at different photometric scales. The algorithm is further specialized for detecting very thin regions. The final segmentation algorithm can detect regions in the image, with varying photometric scales, sizes and arbitrary geometric properties. The properties of the algorithm are experimentally verified on synthetic and real images
Object Tracking Using Globally Coordinated Nonlinear Manifolds

We present a dynamic inference algorithm in a globally parameterized nonlinear manifold and demonstrate it on the problem of visual tracking. An appearance manifold is usually nonlinear, embedded in a high dimensional space, and can be approximated by a mixture of locally linear models. Existing methods for nonlinear dimensionality reduction, which map an appearance manifold to a single low dimensional coordinate system, preserve only spatial relationships among manifold points and render low dimensional embeddings rather than mapping functions. In this paper, we parameterize the mixture of linear appearance subspaces of an object in a global coordinate system, and apply it to visual tracking using a Rao-Blackwellized particle filter. Experimental results demonstrate that the proposed approach performs well on object tracking problem in scenes with significant clutter and temporary occlusions which pose difficulties for other methods
Octree generation from silhouette views of an object

Octrees are used in many 3-D representation problems because they provide a compact data structure, allow rapid access to information, and implement efficient data manipulation algorithms. The initial acquisition of the 3-D information, however, is a common problem. This paper describes an algorithm to construct the octree representation of a 3-D object from silhouette images of the object. The images must be obtained from nine viewing directions corresponding to the three "face-on" and six "edge-on" views of an upright cube. The execution time is found to be linear in the number of nodes in the octree.
Estimation of motion and structure of planar surfaces from a sequence of monocular images

An algorithm is presented which estimates 10 parameters for motion and structure of a rigid planar patch given point correspondences in a monocular image sequence under perspective projection. The rotational velocity is assumed constant and the rotation center arbitrary. The algorithm mainly consists of two steps. First, the 3-D space of ( omega /sub x/, omega /sub y/, omega /sub z/) is searched exhaustively and for each ( omega /sub x/, omega /sub y/, omega /sub z/) all the other parameters with the value of an objective function are computed linearly. some of the ( omega /sub x/, omega /sub y/, omega /sub z/) and the corresponding structure values are used as the initial guesses in the second step. The objective function is iteratively minimized with respect to five variables for rotation and structure. The solution corresponding to the global minimum is used to obtain least squares estimates of the remaining unknowns, for translation and rotation center. It was experimentally found that the objective function converges well so that the 3-D space need not be densely searched. Results are presented for three image sequences, two simulated and one real.<<ETX>>
A comparative study of stereo, vergence, and focus as depth cues for active vision

The performances of the binocular cues of stereo, vergence, and the monocular cue of focus for range estimation using an active vision system are compared. The performance of each cue is characterized by its sensitivity to errors in the imaging parameters. The effect of random quantization errors is expressed in terms of the standard derivation of the resulting depth error. The effect of systematic calibration errors on estimation using each cue is studied. Performance characterization of each cue is shown to be useful for active control of the imaging parameters to improve the accuracy of the estimated range. Methods to integrate the use of the cues in order to overcome their individual limitations are discussed.<<ETX>>
A computer vision system for monitoring the energy efficiency of intermodal trains

Intermodal trains are typically the fastest trains operated by North American freight railroads. It is thus ironic that these trains tend to have the poorest aerodynamic characteristics. Because of constraints imposed by equipment design and diversity, there are often large gaps between intermodal loads and these trains incur greater aerodynamic penalties and increased fuel consumption compared to other trains. We conducted train energy analyses of the most common intermodal train configurations operated in North America. It was found that matching intermodal loads with cars of appropriate length reduces the gap length thereby improving airflow. Properly matching cars with loads also avoids use of cars that are longer and thus heavier than necessary. For double stack containers on well cars, train resistance may be reduced by as much as 9% and fuel savings by 0.52 gallon per mile per train. Proper loading of intermodal trains is therefore important to improving energy efficiency. We have developed a wayside machine vision system that automatically scans passing trains and assesses the aerodynamic efficiency of the loading pattern. Machine vision algorithms are used to analyze these images and detect and measure gaps between loads and develop a quantitative index of the loading efficiency of the train. Integration of this metric that we call "slot efficiency" can provide intermodal terminal managers feedback on loading performance for trains and be integrated into the software support systems used for loading assignment
Scale-invariant region-based hierarchical imagematching

This paper presents an approach to scale-invariant image matching. Given two images, the goal is to find correspondences between similar subimages, e.g., representing similar objects, even when the objects are captured under large variations in scale. As in previous work: similarity is defined in terms of geometric, photometric and structural properties of regions, and images are represented by segmentation trees that capture region properties and their recursive embedding. Matching two regions thus amounts to matching their corresponding subtrees. Scale invariance is aimed at overcoming two challenges in matching two images of similar objects. First, the absolute values of many object image properties may change with scale. Second, some of the finest details visible in the high-zoom image may not be visible in the coarser scale image. We normalize the region properties associated with one of the subtrees to the corresponding properties of the root of the other subtree. This makes the scales of objects represented by the two subtrees equal, and also decouples this scale from that of the entire scene. We also weight contributions of subregions to the total similarity of their parent regions by the relative area the subregions occupy within the parents. This reduces the penalty for not being able to match fine-resolution details present within only one of the two regions, since the penalty will be down-weighted by the relatively small area of these details. Our experiments demonstrate invariance of the proposed algorithm to large changes in scale.
Shape Representation Using a Generalized Potential Field Model

This paper is concerned with efficient derivation of the medial axis transform of a 2D polygonal region. Instead of using the shortest distance to the region border, a potential field model is used for computational efficiency. The region border is assumed to be charged and the valleys of the resulting potential field are used to estimate the axes for the medial axis transform. The potential valleys are found by following the force field, thus, avoiding 2D search. The potential field is computed in closed form using equations of the border segments. The simple Newtonian potential is shown to be inadequate for this purpose. A higher order potential is defined which decays faster with distance than the inverse of distance. It is shown that as the potential order becomes arbitrarily large, the axes approach those computed using the shortest distance to the border. Algorithms are given for the computation of axes, which can run in linear parallel time for part of the axes having initial guesses. Experimental results are presented for a number of examples.
Two-channel predictive multiple description coding

This paper presents a multiple description (MD) video codec based on the principles side-information coding. In particular, we highlight certain key components of the codec design that contribute significantly to the rate-distortion performance of the proposed codec. These include the use of randomized permutations of the quantization codebook in conjunction with binary LDPC codes for partitioning the available bit-rate among the coefficient bit-planes. Another key component of the proposed codec is the use of pdf estimation for improved decoder reconstruction. Lastly, we use a bank of sequential LDPC decoders to efficiently decode the transmitted coset information. Empirical evaluation demonstrates the superior performance of the proposed codec for the communication of encoded video over packet erasure channels.
A new wavelet-based scheme for watermarking images

A new method for digital image watermarking which does not require the original image for watermark detection is presented. Assuming that we are using a transform domain spread spectrum watermarking scheme, it is important to add the watermark in select coefficients with significant image energy in the transform domain in order to ensure non-erasability of the watermark. Previous methods, which did not use the original in the detection process, could not selectively add the watermark to the significant coefficients, since the locations of such selected coefficients can change due to image manipulations. Since watermark verification typically consists of a process of correlation which is extremely sensitive to the relative order in which the watermark coefficients are placed within the image, such changes in the location of the watermarked coefficients was unacceptable. We present a scheme which overcomes this problem of "order sensitivity". Advantages of the proposed method include (i) improved resistance to attacks on the watermark, (ii) implicit visual masking utilizing the time-frequency localization property of the wavelet transform and (iii) a robust definition for the threshold which validates the watermark. We present results comparing our method with previous techniques, which clearly validate our claims.
On cosine-fourth and vignetting effects in real lenses

This paper has been prompted by observations of disparities between the observed fall-off in irradiance for off-axis points and that accounted for by the cosine-fourth and vignetting effects. A closer examination of the image formation process for real lenses revealed that even in the absence of vignetting a point light source does not uniformly illuminate the aperture, an effect known as pupil aberration. For example, we found the variation for a 16 mm lens to be as large as 31% for a field angle of 10/spl deg/. In this paper, we critically evaluate the roles of cosine-fourth and vignetting effects and demonstrate the significance of the pupil aberration on the fall-off in irradiance away from image center. The pupil aberration effect strongly depends on the aperture size and shape and this dependence has been demonstrated through two sets of experiments with three real lenses. The effect of pupil aberration is thus a third important cause of fall in irradiance away from the image center in addition to the familiar cosine-fourth and vignetting effects, that must be taken into account in applications that rely heavily on photometric variation such as shape from shading and mosaicing.
Segmentation of periodically moving objects

We present a new approach for the identification and segmentation of objects undergoing periodic motion. Our method uses a combination of maximum likelihood estimation of the period, and segments moving objects using correlation of image segments over an estimated period of interest. Correlation provides the best locations of the moving objects in each frame. Segmentation tree provides the image segments at multiple resolutions. We ensure that children regions and their parent regions have the same period estimates. We show results of testing our method on real videos.