OpenRaiser/Intern-Atlas huggingface dataset:
Backpack: Detection of People Carrying Objects using Silhouettes
Authors: Ismail Haritaoglu, Ross Cutler, David Harwood, Larry S. Davis
Venue: ICCV
Year: 1999

We described a video-rate surveillance algorithm to detect and track people from a stationary camera, and to determine if they are carrying objects or moving unencumbered. The contribution of the paper is the shape analysis algorithm that both determines if a person is carrying an object and segments the object from the person so that it can be tracked, e.g., during an exchange of objects between two people. As the object is segmented an appearance model of the object is constructed. The method combines periodic motion estimation with static symmetry analysis of the silhouettes of a person in each frame of the sequence. Experimental results demonstrate robustness and real-time performance of the proposed algorithm.
Camera Calibration and the Search for Infinity
Authors: Richard I. Hartley, Lourdes de Agapito, Ian D. Reid 0001, Eric Hayman
Venue: ICCV
Year: 1999

This paper considers the problem of self-calibration of a camera from an image sequence in the case where the camera's internal parameters (most notably focal length) may change. The problem of camera self-calibration from a sequence of images has proven to be a difficult one in practice, due to the need ultimately to resort to non-linear methods, which have often proven to be unreliable. In a stratified approach to self-calibration, a projective reconstruction is obtained first and this is successively refined first to an affine and then to a Euclidean (or metric) reconstruction. It has been observed that the difficult step is to obtain the affine reconstruction, or equivalently to locate the plane at infinity in the projective coordinate frame. The problem is inherently non-linear and requires iterative methods that risk not finding the optimal solution. The present paper overcomes this difficulty by imposing chirality constraints to limit the search for the plane at infinity to a 3-dimensional cubic region of parameter space. It is then possible to carry out a dense search over this cube in reasonable time. For each hypothesised placement of the plane at infinity, the calibration problem is reduced to one of calibration of a nontranslating camera, for which fast non-iterative algorithms exist. A cost function based on the result of the trial calibration is used to determine the best placement of the plane at infinity. Because of the simplicity of each trial, speeds of over 10,000 trials per second are achieved on a 256 MHz processor. It is shown that this dense search allows one to avoid areas of local minima effectively and find global minima of the cost function.
3D Pose Tracking with Linear Depth and Brightness Constraints
Authors: Michael Harville, Ali Rahimi, Trevor Darrell, Gaile G. Gordon, John Woodfill
Venue: ICCV
Year: 1999

This paper explores the direct motion estimation problem assuming that video-rate depth information is available, from either stereo cameras or other sensors. We use these depth measurements in the traditional linear brightness constraint equations, and we introduce a new depth constraint equation. As a result, estimation of certain types of motion, such as translation in depth and rotations out of the image plane, becomes more robust. We derive linear brightness and depth change constraint equations that govern the velocity field in 3-D for both perspective and orthographic camera projection models. These constraints are integrated jointly over image regions according to a rigid-body motion model, yielding a single linear system to robustly track 3D object pose. Results are shown for tracking the pose effaces in sequences of synthetic and real images.
Zoom-Invariant Tracking using Points and Lines in Affine Views - An Application of the Affine Multifocal Tensors
Authors: Eric Hayman, Torfi Thórhallsson, David William Murray 0001
Venue: ICCV
Year: 1999

This paper describes methods for tracking using point and line features in affine views to provide fundamental invariance to changes of focal length. It first demonstrates how an earlier method of transfer-based tracking using spatio-temporal matching of point features in a stereo active head is indeed zoom-invariant. In order to also make use of lines the paper then illustrates how the affine tri- and quadrifocal tensors may be applied to tracking with zoom in monocular and stereo systems respectively. The usefulness of the tensors is evident from their ability to transfer a fixation point in two uncalibrated images into novel views. Whereas the trifocal tensor is already familiar and in common use for matching and reconstruction we believe this to be the first practical application of a quadrifocal tensor. We develop expressions for affine tri- and quadrifocal tensors, and using novel affine specializations of existing projective algorithms we show how computation of the tensors is faster simpler and more stable. Experiments on real images are presented.
Sensitivity Analysis for Object Recognition from Large Structural Libraries
Authors: Benoit Huet, Edwin R. Hancock
Venue: ICCV
Year: 1999

The paper studies the structural sensitivity of line pattern recognition using shape graphs. We compare the recognition performance for four different algorithms. Each algorithm uses a set of pairwise geometric attributes and a neighbourhood graph to represent the structure of the line patterns. The first algorithm uses a pairwise geometric histogram, the second uses a relational histogram on the edges of the shape graph, the third compares the set of attributes on the edges of the shape graph and the final algorithm compares the arrangement of line correspondences using graph matching. The different algorithms are compared under line deletion, line addition, line fragmentation and line end point measurement errors. It is the graph matching algorithm which proves to be the most effective.
Affine Reconstruction from Monocular Vision in the Presence of a Symmetry Plane
Authors: Du Q. Huynh
Venue: ICCV
Year: 1999

This paper reports a closed-form solution for reconstructing a scene up to an affine transformation from a single image in the presence of a symmetry plane. Unlike scene reconstruction in stereo vision, the affine reconstruction process discussed in this paper does not require any knowledge about camera parameters or camera orientation relative to the scene, so camera self-calibration is totally eliminated. By setting in the scene a plane mirror which creates lateral symmetric world points for an uncalibrated, perspective camera to capture, the linear equations involved in the reconstruction process can be derived from two sets of similar triangles. The affine reconstruction is relative to an arbitrary affine coordinated frame implicitly defined on the mirror plane. Also involved in the process are the estimation of the epipole and recovery of the image-to-mirror plane homography. Implementation on estimating the epipole is detailed. A real experiment is presented to demonstrate the reconstruction.
Finding People by Sampling
Authors: Sergey Ioffe, David A. Forsyth
Venue: ICCV
Year: 1999

We show how to use a sampling method to find sparsely clad people in static images. People are modeled as an assembly of nine cylindrical segments. Segments are found using an EM algorithm and then assembled into hypotheses incrementally, using a learned likelihood model. Each assembly step passes on a set of samples of its likelihood to the next; this yields effective pruning of the space of hypotheses. The collection of available nine-segment hypotheses is then represented by a set of equivalence classes, which yield an efficient pruning process. The posterior for the number of people is obtained from the class representatives. People are counted quite accurately in images of real scenes using a MAP estimate. We show the method allows top-down as well as bottom up reasoning. While the method can be overwhelmed by very large numbers of segments, we show that this problem can be avoided by quite simple pruning steps.
Recognition of Multi-Agent Interaction in Video Surveillance
Authors: Yuri A. Ivanov, Aaron F. Bobick
Venue: ICCV
Year: 1999

This paper describes a probabilistic syntactic approach to the detection and recognition of temporally extended activities and interactions between multiple agents. A complete system consisting of an adaptive tracker, an event generator and the parser performs segmentation and labelling of a surveillance video of a parking lot; the system correctly identifies activities such as pick-up and drop-off, which involve person-vehicle interactions. The main contributions of this paper are extending the parsing algorithm to handle multi-agent interactions within a single parser, providing a general mechanism for consistency-based pruning, and developing an efficient incremental parsing algorithm.
Posture Estimation using Structure and Motion Models
Authors: Yoshio Iwai, Kenichi Ogaki, Masahiko Yachida
Venue: ICCV
Year: 1999

Sensing of human motion is very important for human-computer interactive applications such as virtual reality, gesture recognition, and communication. A vision system is suitable for human-computer interaction since this involves passive sensing and the system can estimate the motion of the user without any discomfort for the user. In this paper, we propose an algorithm for fast posture estimation of the user from an image sequence by using the position information of the hands and head. Our algorithm is founded on a model based method. The parameters of a geometric model are calculated from human kinematics. It is inadequate to obtain a unique solution from the image information such as position of the head and hands. The unknown parameters are predicted by the motion models and the previous posture parameters, then the unknown parameters are adjusted by a minimization method.
Globally Optimal Regions and Boundaries
Authors: Ian Jermyn, Hiroshi Ishikawa 0002
Venue: ICCV
Year: 1999

We propose a new form of energy functional for the segmentation of regions in images, and an efficient method for finding its global optima. The energy can have contributions from both the region and its boundary, thus combining the best features of region- and boundary-based approaches to segmentation. By transforming the region energy into a boundary energy, we can treat both contributions on an equal footing, and solve the global optimization problem as a minimum mean weight cycle problem on a directed graph. The simple, polynomial-time algorithm requires no initialization and is highly parallelizable.
Critical Motions and Ambiguous Euclidean Reconstructions in Auto-Calibration
Authors: Fredrik Kahl
Venue: ICCV
Year: 1999

The motions that lead to ambiguous Euclidean reconstructions in auto-calibration are investigated. Several auto-calibration constraints are considered: vanishing skew, known aspect ratio and internally calibrated cameras except for unknown focal lengths. We give a complete description of such critical motions in terms of algebraic manifolds and, in many cases, an explicit, geometric description for any number of cameras. For example, in the case of internally calibrated cameras except for unknown focal lengths, the only motions for which an affine reconstruction is ambiguous are either (i) rotations around (at most) two fired camera centres, or (ii) a planar motion on a conic with the optical axis tangent to the conic, or (iii) translation along the optical axis with arbitrary rotations around the optical axis. Moreover some practically important cases are also discussed.
Accuracy Bounds and Optimal Computation of Homography for Image Mosaicing Applications
Authors: Ken-ichi Kanatani, Naoya Ohta
Venue: ICCV
Year: 1999

We describe a theoretically optimal algorithm for computing the homography between two images in relation to image mosaicing applications. First, we derive a theoretical accuracy bound based on a mathematical model of image noise and do simulation to confirm that our renormalization technique effectively attains that bound; our algorithm is optimal in that sense. Then, we apply our technique to mosaicing of images with small overlaps. By using real images, we show how our algorithm reduces the instability of the image mapping.
Robust Sequence Proximity Estimation by Radial Distance Hashing
Authors: Michael Kertesz, Yehezkel Yeshurun
Venue: ICCV
Year: 1999

There is a recent growing interest in image analysis of multiple views of a scene, often involving aspects of reconstruction, mosaicing and new view generation. As the availability of multiple camera systems augments, we suggest that such tasks could be carried out where the image source is a set of unsynchronized and uncalibrated cameras moving arbitrarily in a 3D scene. In order to make efficient use of this data, it is necessary to define a measure of inter-sequence proximity. We suggest such a measure, based on pure 2D analysis, namely the ratios between image-space distances among a set of feature points. We show this measure to be sound, and propose a simple iterative method to robustly estimate the relative positions of the set of moving cameras, even in the presence of a substantial amount of noise, and without computing egomotion.
Calibration of Hand-Held Camera Sequences for Plenoptic Modeling
Authors: Reinhard Koch, Marc Pollefeys, Benno Heigl, Luc Van Gool, Heinrich Niemann
Venue: ICCV
Year: 1999

We focus on the calibration of very long image sequences from a hand-held camera that samples the viewing sphere of a scene. View sphere sampling is important for plenoptic (image-based) modeling that captures the appearance of a scene by storing images from all possible directions. The plenoptic approach is appealing since it allows, in principle, fast scene rendering of scenes with complex geometry and surface reflections, without the need for an explicit geometrical scene model. However the acquired images have to be calibrated, and current approaches mostly use pre-calibrated acquisition systems. This limits the generality of the approach. We propose using an uncalibrated hand-held camera only. The image sequence is acquired by simply waving the camera around the scene objects, creating a zigzag scan path over the viewing sphere. We extend the sequential camera tracking of an existing structure-from-motion approach to the calibration of a mesh of viewpoints. Novel views are generated by piecewise mapping and interpolating the new image from the nearest viewpoints according to the viewpoint mesh. Local depth map estimates enhance the rendering process. Extensive experiments with ground truth data and hand-held sequences confirm the performance of our approach.
Modeling the Process of Aging in Face Images
Authors: Andreas Lanitis, Christopher J. Taylor 0001, Timothy F. Cootes
Venue: ICCV
Year: 1999

The process of ageing causes significant alterations in the facial appearance of individuals. When compared with other sources of variation in face images (e.g. variation due to changes in pose and expression), appearance variation due to ageing displays some unique characteristics. For example ageing variation is specific to a given individual, it occurs slowly and it is affected significantly by other factors, such as the health, gender and the lifestyle of the individual. In this paper we describe how the effects of ageing on facial appearance can be explained using a parameterized statistical model. We present experimental results to show that reasonably accurate estimates of age can be made for unseen images. We also show that we can improve our results significantly by taking into account the fact that different individuals age in different ways and by considering the effect of lifestyle. We also demonstrate how the proposed framework can be used for simulating ageing effects on new face images, in order to predict how an individual might look like in the future, or how he/she used to look in the past. Experimental and visual results on simulation of age effects are presented.
The Visual Hull of Curved Objects
Authors: Aldo Laurentini
Venue: ICCV
Year: 1999

The visual hull is a geometric tool which relates the 3D shape of a concave object to its silhouettes or shadows. This paper deals with the computation of the visual hull of objects bounded by smooth curved surfaces. We show that the surfaces which bound the visual hull are surfaces relevant for the construction of the aspect graph of the object, and that the algorithms for computing the aspect graph of curved objects can be exploited for computing their visual hull.
Modeling Bayesian Estimation for Deformable Contours
Authors: Stan Z. Li, Juwei Lu
Venue: ICCV
Year: 1999

A novel trainable snake model called EigenSnake, is presented in the Bayesian framework. In the EigenSnake, prior knowledge of a specific object shape, such as that of face outlines and facial features, is derived from a training set of the shape and incorporated into a Bayesian snake model in the form of the prior distribution. Further, a "shape space", which is constructed on the basis of a set of eigenvectors obtained from principle component analysis, is used to restrict and stabilize the search for the optimal solution. The effectiveness is demonstrated by experiments, which shows that the EigenSnake produces more reliable and accurate results than existing models.
United Snakes
Authors: Jianming Liang, Tim McInerney, Demetri Terzopoulos
Venue: ICCV
Year: 1999

Since their debut in 1987, snakes (active contour models) have become a standard image analysis technique with several variants now in common use. We present a portable, reusable software package called "United Snakes". The package unites the most popular snake variants, including finite difference, B-spline, and Hermite polynomial snakes within the mathematical framework of a general finite element formulation with a choice of shape functions. The package furthermore incorporates a recently proposed snake-like technique known as "livewire". We integrate snakes and livewire by introducing an effective method for imposing hard constraints on snakes. Our experiments demonstrate that snakes and livewire have complementary strengths and that their union offers a more powerful tool for interactive image analysis, especially for medical imaging applications. United Snakes is implemented in Java as a JavaBean so that it can easily be integrated in end user application systems.
A Representation of Specular Appearance
Authors: Stephen Lin, Sang Wook Lee
Venue: ICCV
Year: 1999

The appearance of an object can vary considerably with changes in illumination conditions. Methods have been developed to describe these differences for diffuse reflection using the Lambertian model, but little work has been done in characterizing specular appearance. Towards a more comprehensive global reflectance descriptor, this paper focuses on a representation of specular appearance based on an approximate specular reflection model derived from Torrance-Sparrow. We propose that under certain illumination and surface conditions local specular structure can be expressed by the logarithms of three intensity-normalized photometric images. The total number of photometric images needed for representing global specular appearance depends on the object surface roughness, and we suggest an illumination planning method for determining the number of images. Experimental results demonstrate the effectiveness of this logarithmic model as a specular descriptor.
Estimation of Diffuse and Specular Appearance
Authors: Stephen Lin, Sang Wook Lee
Venue: ICCV
Year: 1999

To account for the variability of object appearance due to differences in illumination, attention has recently been focused on representing the set of images for all possible lighting conditions. Approaches that address this problem have primarily focused on lighting differences for diffuse reflection using the Lambertian model; however specular reflections can additionally present considerable disparity in appearance. We present a method for representing illumination appearance for both diffuse and specular reflections for objects of uniform surface roughness using four photometric images. This approach uses separation of reflection components, extracts surface reflectances and roughness, and produces arbitrary lighting images without explicit computation of surface shape. Experimental results demonstrate the validity of the proposed method for constructing diffuse and specular appearances.
Correspondenceless Motion Estimation from Range Images
Authors: Yonghuai Liu, Marcos A. Rodrigues 0001
Venue: ICCV
Year: 1999

Estimation of rigid-body motion parameters in computer vision is normally performed from image correspondences between two coordinate frames. A large number of methods and algorithms have been proposed based on that such correspondences are known. Unfortunately, the establishment of correspondences is often time-consuming and, in many cases, impossible. In this paper, we propose a novel correspondenceless motion estimation algorithm based on the cross matrix. For a comparative study, we also implemented a correspondenceless motion estimation algorithm based on the scatter matrix. Experimental results have demonstrated that our method is more accurate and robust than the scatter matrix-based algorithm.
Specularities on Surfaces with Tangential Hairs or Grooves
Authors: Rong Lu, Jan J. Koenderink, Astrid M. L. Kappers
Venue: ICCV
Year: 1999

Specularities on surfaces with tangential hairs or grooves are readily observable in nature. Examples of such phenomena are the arched or looped highlights observed on horses and on human heads and the linear or curved specularities observed on parts of industrial machinery that have tangential grooves. We investigate the geometry of curvilinear specularities on surfaces of different curvature with tangential hairs or grooves of different orientation, under controlled lighting and viewing conditions. First the nature of these specularities is investigated qualitatively. Then specularities on parametric surfaces and hair or groove orientations are calculated for some specific cares. Explicit calculations of specularities on some special surfaces, cylinders, cones, and spheres, are verified by photographs of the reflections. Aspects of the work are applicable to computer graphics and can be utilized for the image interpretation of surface specularities.
Removal of Translation Bias when using Subspace Methods
Authors: W. James MacLean
Venue: ICCV
Year: 1999

Given estimates of the motion field (optic flow) from an image sequence, it is possible to recover translational direction, T/spl I.oarr/, using a variety of techniques. One such technique, known as "subspace methods, generates constraints which are perpendicular to T/spl I.oarr/, so that two distinct constraints allow a solution for T/spl I.oarr/. In practice many constraints are used in a least-squares solution, but it has been observed that the recovered estimates for T/spl I.oarr/ are biased towards the optical axis. While the cause of the bias is well known, previous attempts to remove it have been flawed. This paper outlines a new method which removes the bias. The technique is simple to apply and computationally efficient.