OpenRaiser/Intern-Atlas huggingface dataset:
Linear and incremental acquisition of invariant shape models from image sequences
Authors: Daphna Weinshall, Carlo Tomasi
Venue: ICCV
Year: 1993

The authors show how to automatically acquire similarity-invariant shape representations of objects from noisy image sequences under a weak perspective. The incremental nature of the method makes it possible to process images one at a time, moving away from the storage-intensive batch methods of the past. It is based on the observation that the trajectories that points on the object form in weak-perspective image sequences are linear combinations of three of the trajectories themselves, and that the coefficients of the linear combinations represent shape in an affine-invariant basis. A nonlinear but numerically sound preprocessing state is added to improve the accuracy of the results even further. Experiments showed that attention to noise and computational techniques improved the shape results substantially with respect to previous methods.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Learning recognition and segmentation of 3-D objects from 2-D images
Authors: John (Juyang) Weng, Narendra Ahuja, Thomas S. Huang
Venue: ICCV
Year: 1993

A framework called Cresceptron is introduced for automatic algorithm design through learning of concepts and rules, thus deviating from the traditional mode in which humans specify the rules constituting a vision algorithm. With the Cresceptron, humans as designers need only to provide a good structure for learning, but they are relieved of most design details. The Cresceptron has been tested on the task of visual recognition by recognizing 3-D general objects from 2-D photographic images of natural scenes and segmenting the recognized objects from the cluttered image background. The Cresceptron uses a hierarchical structure to grow networks automatically, adaptively, and incrementally through learning. The Cresceptron makes it possible to generalize training exemplars to other perceptually equivalent items. Experiments with a variety of real-world images are reported to demonstrate the feasibility of learning in the Cresceptron.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Active exploration: Knowing when we're wrong
Authors: Peter Whaite, Frank P. Ferrie
Venue: ICCV
Year: 1993

Many strategies in computer vision assume the existence of general purpose models that can be used to characterize a scene or environment at various levels of abstraction. The usual assumptions are that a selected model is competent to describe a particular attribute and that the parameters of this model can be estimated by interpreting the input data in an appropriate manner. The authors consider the problem of determining when these assumptions break down so that an alternate model may be considered or further interpretation of data performed. Specifically, how this can be accomplished is analyzed within the framework of an approach that actively builds a description of the environment from several different viewpoints. It is shown that a gaze planning strategy used to minimize model parameter variance can also be used to decide whether the model itself provides an adequate description of the environment.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Active and intelligent sensing of road obstacles: Application to the European Eureka-PROMETHEUS project
Authors: Ming Xie, Laurent Trassoudaine, Joseph Alizon, Monique Thonnat, Jean Gallice
Venue: ICCV
Year: 1993

The authors address the problem of road obstacle detection. A sensor composed of an eyesafe laser range finder coupled with a charge coupled device (CCD) camera is proposed. This sensor is mounted in front of a vehicle. The basic idea is to first determine 2-D visual targets in intensity images of the camera. The range finder is then used not only to confirm or reject the real existence of the detected visual targets but also to acquire 3-D information of the confirmed visual targets. The central problem of this strategy is the method of detection of 2-D visual targets from intensity images of a road scene. In the method, line segments are considered as significant features. The concept of a line segment of interest and the concept of a dominant line segment are used. Two-imensional visual targets can be effectively determined with the help of the identification of the dominant line segments in an image. The range finder was used to confirm or reject a 2-D visual target.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
A robust active contour model with insensitive parameters
Authors: Gang Xu, Eigo Segawa, Saburo Tsuji
Venue: ICCV
Year: 1993

Active contours, known as snakes, have found wide application since their first introduction in 1987 by M. Kass, A. Witkin and D. Terzopoulos. However, one problem with the current models is that the performance depends on proper internal parameters and initial contour position, which, unfortunately, cannot be determined a priori. It is usually difficult to tune internal parameters and initial contour position. The problem results from the fact that the internal normal force at each point of a contour is also a function of contour shape. To solve this problem, the authors propose to compensate for this internal normal force so as to make it independent of shape. As a result the new model works robustly with no necessity for tuning internal parameters and can converge to high curvature points like corners.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
An extension of Marr's signature based edge classification and other methods determining diffuseness and height of edges, and bar edge width
Authors: Wei Zhang, Fredrik Bergholm
Venue: ICCV
Year: 1993

The authors classify edges with respect to diffuseness and profile type by using a tool evolved from scale space methodology called signatures. The method also enables the user to measure degree of diffuseness, height of edges, and bar edge width. The Gaussian difference signatures and apparent width signatures used are defined. To sift out the major edges, subsets of edge pixels must be selected. For describing the local gray level, landscape averaging needs to be done in a noncommittal fashion, as opposed to fitting a specific function blindly to data. Edge focusing, which is a coarse-to-fine traversal of brightness changes, deals with the subsets, whereas signatures may be thought of as a kind of reasonably cleverly done averaging. This method is of importance for distinguishing between illumination phenomena and object edges, performing depth-from-focus in single images, and in junction analysis.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Automatic feature point extraction and tracking in image sequences for unknown camera motion
Authors: Qinfen Zheng, Rama Chellappa
Venue: ICCV
Year: 1993

An automatic ego motion compensation based feature detection and correspondence algorithm is presented. For image sequences taken from a moving camera, feature displacement over consecutive frames can be approximately decomposed into two components: the displacement due to camera motion, which can be compensated for by image rotation, scaling, and translation; and the displacement due to object motion and/or perspective projection. The authors introduce a two-step approach. First, the motion of the camera is compensated for by using a computational vision based image registration algorithm. Then consecutive frames are transformed to the same coordinate system and the feature correspondence problem is solved as though for a stationary camera. Feature points are detected using a Gabor wavelet decomposition and a local interaction based algorithm. Methods for subpixel accuracy feature matching and tracking are introduced. Experimental results on a real image sequence are presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Robust 3D-3D pose estimation
Authors: Xinhua Zhuang, Yan Huang 0010
Venue: ICCV
Year: 1993

The authors focus on the robust 3D-3D single and multiple pose estimation problems. The robust 3D-3D single pose estimation problem was formulated by R. M. Haralick et al. (1989) as a general regression in terms of a contaminated Gaussian error noise model. The robust 3D-3D multiple pose estimation problem appears much more difficult. This problem is formulated as a series of general regressions involving successively decreasing data size, with each regression related to one particular pose of interest. Since the first few regressions may carry a highly contaminated Gaussian error noise model, a very robust estimator called the MF-estimator, given by X. Zhuang et al. (1992), is used to solve each regression for each desired pose estimation. Computer experiments with real imagery and simulated data were conducted and results are promising.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Eliciting qualitative structure from image curve deformations
Authors: Andrew Zisserman, Andrew Blake 0001, Charlie Rothwell, Luc Van Gool, Marc Van Diest
Venue: ICCV
Year: 1993

A family of qualitative methods is described that determines structure of curves in a scene from their image projections in two or more views. For example, plane curves are distinguished from space curves, and space curves from contour generators. The novelty of the approach is that first, it is unaffected by camera intrinsic parameters, so calibration is not required; second, it is also unaffected by camera motion, so viewer motion need not be known; and third, curves need not be matched point by point. Qualitative scene descriptions can be determined using relative measurements, and affine or projective properties alone. The practical power of this family of methods is demonstrated using a real-time vision system based on B-spline snake-tracking.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Active Fixation Using Attentional Shifts, Affine Resampling, and Multiresolution Search
Authors: A. Lynn Abbott, Bibo Zheng
Venue: ICCV
Year: 1995

Presents a new approach for fixing two cameras at a single location in a 3D scene. Fixation requires the detection of binocular disparity for a single point of interest in the scene so that vergence control can reduce that disparity to zero. Most existing systems use area-based matching, since feature-based matching is computationally prohibitive. Unfortunately, the area-based approach does not perform well when confronted with steeply inclined surfaces, occlusions, repeating patterns or featureless image regions. The method presented in this paper utilizes attentional shifts and affine resampling to combat these problems. These are integrated with adaptive window-size control and coarse-to-fine correlation-based searching. The effectiveness of the approach for complex scenes is demonstrated with several stereo image pairs.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Seeing Behind the Scene: Analysis of Photometric Properties of Occluding Edges by the Reversed Projection Blurring Model
Authors: Naoki Asada, Hisanaga Fujiwara, Takashi Matsuyama
Venue: ICCV
Year: 1995

This paper analyzes photometric properties of occluding edges and proves that (1) we can observe surface edges on the farther object located close to the occluding edge even if they are occluded by the nearer object, (2) the image of an occluding edge coincides with that of a surface edge on the nearer object if the brightness of the farther object is uniform around the occluding edge. First, we propose a blurring model named the reversed projection blurring model to analyze photometric properties of blurring phenomena of an occluding edge. Using this model, the theoretical proof of the two properties mentioned above is given. Finally, experimental results in real world environments demonstrate the validity of our blurring model as well as the observability of the photometric properties of occluding edges.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Layered Representation of Motion Video Using Robust Maximum-Likelihood Estimation of Mixture Models and MDL Encoding
Authors: Serge Ayer, Harpreet S. Sawhney
Venue: ICCV
Year: 1995

Representing and modeling the motion and spatial support of multiple objects and surfaces from motion video sequences is an important intermediate step towards dynamic image understanding. One such representation, called layered representation, has recently been proposed. Although a number of algorithms have been developed for computing these representations, there has not been a consolidated effort into developing a precise mathematical formulation of the problem. This paper presents one such formulation based on maximum likelihood estimation (MLE) of mixture models and the minimum description length (MDL) encoding principle. The three major issues in layered motion representation are: (i) how many motion models adequately describe image motion, (ii) what are the motion model parameters, and (iii) what is the spatial support layer for each motion model.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Scale-Space from Nonlinear Filters
Authors: J. Andrew Bangham, Paul D. Ling, Richard W. Harvey
Venue: ICCV
Year: 1995

Decomposition by extrema is put into the context of linear vision systems and scale-space. One dimensional discrete M- and N-sieves neither introduce new edges as the scale increases nor create new extrema. They share this property with diffusion based filters. Furthermore M- and N-sieve algorithms are extremely fast with order complexity n. Used to decompose an image, the resulting granularity is appropriate for pattern recognition.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Recognition Using Region Correspondences
Authors: Ronen Basri, David W. Jacobs
Venue: ICCV
Year: 1995

A central problem in object recognition is to determine the transformation that relates the model to the image, given some partial correspondence between the two. This is useful in determining whether an object is present in an image, and if so, in determining where the object is. We present a novel method of solving this problem that uses region information. In our approach, the model is divided into volumes and the image is divided into regions. Given a match between subsets of volumes and regions (without any explicit correspondence between different pieces of the regions), the alignment transformation is computed. The method applies to planar objects under similarity, affine and projective transformations and to projections of 3D objects undergoing affine and projective transformations.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Active Visual Navigation Using Non-Metric Structure
Authors: Paul A. Beardsley, Ian D. Reid 0001, Andrew Zisserman, David William Murray 0001
Venue: ICCV
Year: 1995

Demonstrates a method of using nonmetric visual information derived from an uncalibrated active vision system to navigate an autonomous vehicle through free-space regions detected in a cluttered environment. The structure of 3-space is recovered modulo an affine transformation using an uncalibrated active stereo head carried by the vehicle. The plane at infinity, necessary for recovering affine structure from projective structure, is found in a novel manner by making controlled rotations of the head. The structure is composed of 3D points obtained by detecting and matching image corners through the stereo image sequence. Considerable care has been taken to ensure that the processing is reliable, robust and automatic. Driveable regions are determined from the projection of the affine structure onto a plane parallel to the ground determined using projective constructs. Two methods of negotiating the regions are explored. The first introduces metric information to allow control of a Euclidean vehicle. The second uses visual servoing of the active head to navigate in the affinely described free-space regions.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Learning Geometric Hashing Functions for Model-Based Object Recognition
Authors: George Bebis, Michael Georgiopoulos, Niels da Vitoria Lobo
Venue: ICCV
Year: 1995

A major problem associated with geometric hashing and methods which have emerged from it is the non-uniform distribution of invariants over the hash space. This problem can affect the performance of the method significantly. Finding a "good" geometric hash function which redistributes the invariants uniformly over the hash space is not easy. In this paper, a new approach is proposed for alleviating the above problem. It is based on the use of an "elastic hash table" which is implemented as a self-organizing feature map neural network (SOFM-NN). In contrast to existing approaches which try to redistribute the invariants over the hash bins, we proceed oppositely, spreading the hash bins over the invariants. During training, the SOFM-NN resembles an elastic net which deforms over the hash space. The objective of the deformation process is to spread more hash bins in hash space areas which are heavily occupied and less hash bins in lower density areas. The advantage of the proposed approach is that it is a process that adapts to the invariants through learning. Hence, it makes absolutely no assumptions about the statistical characteristics of the invariants and the geometric hash function is actually computed through learning. Furthermore, the well known "topology preserving" property of the SOFM-NN guarantees that the computed geometric hash function should be well behaved. Finally, the proposed approach is inherently parallelizable.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Recovering Object Surfaces from Viewed Changes in Surface Texture Patterns
Authors: Peter N. Belhumeur, Alan L. Yuille
Venue: ICCV
Year: 1995

Explores the reconstruction of object surfaces from viewed changes in surface texture patterns. Our approach differs from those in the past in that instead of simply producing local estimates of the surface orientation, our algorithm recovers complete surfaces. Past approaches only found the surface orientation locally and, therefore, did not take advantage of the surface integrability constraint. Our algorithm does not assume that the surface texture pattern is isotropic, and it does not assume that the viewed surface is at some point fronto-parallel. Furthermore, our algorithm has mechanisms for handling texture boundaries and, consequently, does not produce erratic results in the regions abutting these boundaries. Results on real images are presented demonstrating the potential of our approach.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Face Recognition from One Example View
Authors: David Beymer, Tomaso A. Poggio
Venue: ICCV
Year: 1995

To create a pose-invariant face recognizer, one strategy is the view-based approach, which uses a set of real example views at different poses. But what if we only have one real view available, such as a scanned passport photo-can we still recognize faces under different poses? Given one real view at a known pose, it is still possible to use the view-based approach by exploiting prior knowledge of faces to generate virtual views, or views of the face as seen from different poses. To represent prior knowledge, we use 2D example views of prototype faces under different rotations. We develop example-based techniques for applying the rotation seen in the prototypes to essentially "rotate" the single real view which is available. Next, the combined set of one real and multiple virtual views is used as example views for a view-based, pose-invariant face recognizer. Oar experiments suggest that among the techniques for expressing prior knowledge of faces, 2D example-based approaches should be considered alongside the more standard 3D modeling techniques.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Stereo in the Presence of Specular Reflection
Authors: Dinkar N. Bhat, Shree K. Nayar
Venue: ICCV
Year: 1995

The problem of accurate depth estimation using stereo in the presence of specular reflection is addressed. Specular reflection, a fundamental and ubiquitous reflection mechanism, is viewpoint dependent and can cause large intensity differences at corresponding points, resulting in significant depth errors. We analyze the physics of specular reflection and the geometry of stereopsis which led us to a relationship between stereo vergence, surface roughness, and the likelihood of a correct match. Given a lower bound on surface roughness, an optimal binocular stereo configuration can be determined which maximizes precision in depth estimation despite specular reflection. However, surface roughness is difficult to estimate in unstructured environments. Therefore, trinocular configurations, independent of surface roughness, are determined such that at each scene point visible to all sensors, at least one stereo pair can compute produce depth. We have developed a simple algorithm to reconstruct depth from the multiple stereo pairs.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Epipole and Fundamental Matrix Estimation Using Virtual Parallax
Authors: Boubakeur Boufama-Seddik, Roger Mohr
Venue: ICCV
Year: 1995

The paper addresses the problem of computing the fundamental matrix which describes a geometric relationship between a pair of stereo images: the epipolar geometry. We propose a novel method based on virtual parallax. Instead of computing directly the 3/spl times/3 fundamental matrix, we compute a homography with one epipole position, and show that this is equivalent to computing the fundamental matrix. Simple equations are derived by reducing the number of parameters to estimate. As a consequence, we obtain an accurate fundamental matrix of rank two with a stable linear computation. Experiments with simulated and real images validate our method and clearly show the improvement over existing methods.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Electronically Directed "Focal" Stereo
Authors: Peter J. Burt, Lambert E. Wixson, Garbis Salgian
Venue: ICCV
Year: 1995

A key to developing computationally efficient stereo vision is the incorporation of intelligent control. Stereo is most effective when it is able to "focus" its analysis on regions and details of a scene that are important to the task at hand, while avoiding less important regions and unnecessary detail. The paper describes two methods for electronically "focusing" stereo measurement through simple image pre-processing. The first allows measurement sensitivity to be adjusted. The second allows the shape of the 3D region in which measurements are gathered to be matched to the shape of surfaces in the scene.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>