Perspective Images Research Articles

An improved algorithm for two-image camera self-calibration and Euclidean structure recovery using absolute quadric

We present an improved algorithm for two-image camera self-calibration and Euclidean structure recovery, where the effective focal lengths of both cameras are assumed to be the only unknown intrinsic parameters. By using the absolute quadric, it is shown that the effective focal lengths can be computed linearly from two perspective images without imposing scene or motion constraints. Moreover, a quadratic equation derived from the absolute quadric is proposed for solving the parameters of the plane at infinity from two images, which upgrades a projective reconstruction to a Euclidean reconstruction.

Saccadic localization in the presence of cues to three-dimensional shape.

Saccades directed to simple two-dimensional (2D) target shapes under instructions to look at the target as a whole land near the center of gravity (COG) of the shape with a high degree of precision (He & Kowler, 1991; Kowler & Blaser, 1995; McGowan, Kowler, Sharma, & Chubb, 1998; Melcher & Kowler, 1999; Vishwanath, Kowler, & Feldman, 2000). This pattern of performance has been attributed to the averaging of visual signals across the shape. Natural objects, however, are three-dimensional (3D), and the shape of the object can differ dramatically from its 2D retinal projection. This study examined saccadic localization of computer-generated perspective images of 3D shapes. Targets were made to appear either 2D or 3D by manipulating shading, context, and contour cues. Average saccadic landing positions (SD approximately 10% eccentricity) fell at either the 2D or 3D COG, and occasionally in between, depending on the nature of the 3D cues and the subject. The results show that saccades directed to objects are not compelled to land at the 2D COG, but can be sensitive to other visual cues, such as cues to 3D structure. One way to account for these results, without abandoning the averaging mechanism that has accounted well for performance with simple 2D shapes, is for saccadic landing position to be computed based on averaging across a weighted representation of the shape in which portions projected to be located at a greater distance receive more weight.

A General Framework for the Selection of World Coordinate Systems in Perspective and Catadioptric Imaging Applications

An imaging system with a single effective viewpoint is called a central projection system. The conventional perspective camera is an example of central projection system. A catadioptric realization of omnidirectional vision combines reflective surfaces with lenses. Catadioptric systems with an unique projection center are also examples of central projection systems. Whenever an image is acquired, points in 3D space are mapped into points in the 2D image plane. The image formation process represents a transformation from ℜ3 to ℜ2, and mathematical models can be used to describe it. This paper discusses the definition of world coordinate systems that simplify the modeling of general central projection imaging. We show that an adequate choice of the world coordinate reference system can be highly advantageous. Such a choice does not imply that new information will be available in the images. Instead the geometric transformations will be represented in a common and more compact framework, while simultaneously enabling newer insights. The first part of the paper focuses on static imaging systems that include both perspective cameras and catadioptric systems. A systematic approach to select the world reference frame is presented. In particular we derive coordinate systems that satisfy two differential constraints (the “compactness” and the “decoupling” constraints). These coordinate systems have several advantages for the representation of the transformations between the 3D world and the image plane. The second part of the paper applies the derived mathematical framework to active tracking of moving targets. In applications of visual control of motion the relationship between motion in the scene and image motion must be established. In the case of active tracking of moving targets these relationships become more complex due to camera motion. Suitable world coordinate reference systems are defined for three distinct situations: perspective camera with planar translation motion, perspective camera with pan and tilt rotation motion, and catadioptric imaging system rotating around an axis going through the effective viewpoint and the camera center. Position and velocity equations relating image motion, camera motion and target 3D motion are derived and discussed. Control laws to perform active tracking of moving targets using visual information are established.

The relationship between the use of kinaesthetic imagery and different visual imagery perspectives

In two studies, we examined the strength of relationship between internal and external visual imagery with kinaesthetic imagery. In Study 1, 56 participants completed the Vividness of Movement Imagery Questionnaire and the Movement Imagery Questionnaire. Pearson's product–moment correlations failed to reveal a significant correlation between external visual imagery and kinaesthetic imagery. However, the correlation between internal visual imagery and kinaesthetic imagery approached significance. In Study 2, the instructional set of the Vividness of Movement Imagery Questionnaire was changed to make the participant the ‘agent’ of the external visual perspective images rather than somebody else. Sixty-four participants completed the two questionnaires. The results indicated a significant correlation between external visual imagery and kinaesthetic imagery (r = 0.60, P <0.01). However, the correlation between internal visual imagery and kinaesthetic imagery was non-significant (r = 0.23, P >0.01). The results are discussed in relation to who is the agent of the image and the processes that may underlie kinaesthetic imagery. The implications for researchers trying to establish the functional, behavioural and neurological differences within, and across, imagery modalities are considered.

Experimental Research about the Proportion of Perspective Image through the Movement of Viewpoint (II)

Experimental Research about the Proportion of Perspective Image through the Movement of Viewpoint (II)

Multiperspective imaging

Our eyes have evolved with perspective optics. Because of this, perspective images seem somewhat natural to our eyes; they're well tailored for human vision. In a perspective image, the objects close to us appear large and in detail, yet we enjoy sweeping wide-range views of distant scenery. Cameras have also evolved with perspective optics. It's natural for the optics of cameras to mimic the human eye. However, our perspective has some unfortunate shortcomings. In particular, our eyes have a limited field of view, and we can only see the world in front of us. Ideally, we could see in all directions at once. Additionally, we can only see one side of an object at a time. But suppose you could see all sides at the same time. In the last few years, some researchers (including ourselves) have investigated techniques that capture multiple perspectives into a single image - a problem known as multiperspective imaging. Multiperspective images are useful for several reasons. The ability to capture a panoramic field of view or both the front and back of an object leads to richer and more complete visualizations. At the same time, these images are well suited for processing in computer vision problems such as stereo reconstruction and motion analysis. The article presents an overview of our work in this area, and our view of multiperspective imaging in general.

The impossibility of affine reconstruction from perspective image pairs obtained by a translating camera with varying parameters

Contrary to claim in literature that affine reconstruction is possible from two images captured by a translating camera with unknown and varying parameters, we show that such a reconstruction is in fact impossible. In other words, knowledge that the camera's motion between two images is just a pure translation is an insufficient piece of information for affine reconstruction.

Extraction of digital elevation models from satellite stereo images through stereo matching based on epipolarity and scene geometry

This paper addresses the problem of generating digital elevation models from satellite images taken by linear pushbroom cameras. Since there exist unique geometric properties for linear pushbroom images, we argue that the conventional DEM generation schemes developed for perspective images are not suitable for satellite images. Using the geometric properties of linear pushbroom images, we design a new matching strategy optimized for linear pushbroom image in three aspects: conjugate search method, correlation patch design and match sequence determination. We will discuss in what aspect conventional approaches and our new approach differ and show how performance has improved by hiring proper techniques. A series of experiments using SPOT panchromatic stereo pairs showed that our approach outperformed conventional approaches in terms of accuracy and processing time.

Mosaicing new views: the crossed-slits projection

We introduce anew kind of mosaicing, where the position of the sampling strip varies as a function of the input camera location. The new images that are generated this way correspond to a new projection model defined by two slits, termed here the Crossed-Slits (X-Slits) projection. In this projection model, every 3D point is projected by a ray defined as the line that passes through that point and intersects the two slits. The intersection of the projection rays with the imaging surface defines the image. X-Slits mosaicing provides two benefits. First, the generated mosaics are closer to perspective images than traditional pushbroom mosaics. Second, by simple manipulations of the strip sampling function, we can change the location of one of the virtual slits, providing a virtual walkthrough of a X-Slits camera; all this can be done without recovering any 3D geometry and without calibration. A number of examples where we translate the virtual camera and change its orientation are given; the examples demonstrate realistic changes in parallax, reflections, and occlusions.

誤差重み付けによる３次元復元形状の補正法

this paper proposes a new method for iteratively correcting three dimensional (3-d) shapes by weighting reconstruction errors when the shape is reconstructed from more than three 2-d perspective images using linear camera models such as weak-or para-perspective cameras. the method can compensate measurement errors by using its variance-covariance matrix, where the measurement errors are composed of random noise and the disparity between the linear camera models and non-linearity of perspective cameras, and can reduce mean reconstruction errors by adjusting the tolerance range of the reconstruction errors in accordance with the measurement error variances and also by eliminating the covariances between these errors. in numerical experiments using synthetic and real images, our method achieves correction results that are almost equivalent to those obtained by using variance-covariance matrices determined by a precise 3-d shape. the method also achieves a considerable amount of correction for both essentially nonlinear camera images and approximately linear camera images if the random noise is not strong and if more than twenty 2-d images are available.

Integrated Laser Measuring System for the Ellipsometric and Photovoltage Characterization of Thin Surface Layers

An integrated computer-based measuring system is designed, assembled, and tested that combines ellipsometry with photovoltage measurements, using a semiconductor laser as the light source. It enables one to simultaneously measure the thickness and photovoltage-related properties of a micrometer-sized region selected in a thin surface layer. The system also gives computer-generated perspective images of the region examined. Both phase and intensity light modulation are provided by an electro-optical modulator operated over a wide frequency range. It is established that combining the two measurement techniques is a useful method for (i) detecting microscopic surface defects which cannot be revealed by purely optical methods and (ii) evaluating the semiconductor properties of thin surface layers.

A Parametric Study of Mental Spatial Transformations of Bodies

Two classes of mental spatial transformation can be distinguished: Object-based spatial transformations are imagined movements of objects; and egocentric perspective transformations are imagined movements of one's point of view. The hypothesis that multiple neural systems contribute to these mental imagery operations was tested with functional MRI. Participants made spatial judgments about pictures of human bodies, and brain activity was analyzed as a function of the judgment required and the time taken to respond. Areas in right temporal, occipital and parietal cortex and the medial superior cerebellum appear to be differentially involved in object-based spatial transformations. Additionally, midline structures and lateral parietal cortex were found to decrease in activity during the spatial reasoning tasks, independently of the judgment required or of the latency of response. The results are discussed in terms of a model of spatial reasoning that postulates specialized subsystems for performing object-based and egocentric perspective image transformations.

Numerical simulation of volcanic plume dispersal from Usu volcano in Japan on 31 March 2000 using PUFF model

In this study, a volcanic ash tracking model called “PUFF” is applied to the actual eruption of Usu volcano on 31 March 2000 in order to infer the movement of airborne ash clouds for aviation safety. The PUFF model was developed and operated by the Alaska Volcano Observatory since the eruption of Redoubt volcano in 1989. The performance of the PUFF model is examined in this study based on the ground truth of the observed distribution of tephra on the ground. According to the model simulation, the ash plume erupted from Usu volcano first moved eastward for the New Chitose International Airport. As the upper air westerly wind gradually shifted to southerly wind, the ash front traveled from Chitose to Nemuro while the subsequent eruption plume directed toward the northeast over Sapporo area. The vertical cross sections and 3-D perspective image of the ash clouds are presented as a function of time. The model simulation was justified by the agreement between the modeled and observed distributions of tephra on the ground. The PUFF model with accurate wind information can simulate the location and the direction of the moving airborne ash cloud on a realtime basis, which may provide crucial information to aviation industry.

Multiple-view line-scan imaging

A novel multiple-view line-scan imaging technique utilising a single area array camera is presented. The camera's imager array is treated as a contiguous set of precisely arranged linescan sensors. The picture information from the columns of selected photosites is cyclically stored in digital memory, while the object under inspection is translated through the field of view of the camera. A number of perspective images (typically 6 to 16) are produced during a single linear translation of the object under inspection. The three-dimensional information, inherent in the resultant perspective images, can be visualised as a smooth object rotation on a video display monitor. It has also been demonstrated that this rotational effect can be incorporated into a dynamic binocular stereoscopic display. This imaging technique was developed to model the geometric imaging properties of a multiple-view line-scan transmission X-ray system intended for security screening applications. The perspective images produced by the visible light experimental system are presented together with a theoretical discussion.

Dynamic stereoscopic X-ray imaging

Abstract A multiple view binocular stereoscopic X-ray imaging technique developed as a part of a feasibility study for a security screening application is presented. The experimental system utilises a single X-ray source and a multiple view line-scan camera incorporating an X-ray image intensifier. This set up is used to simulate coplanar configurations of discrete linear X-ray detector arrays. A number of perspective images (typically 6–16) are produced during a single linear translation of the object under inspection. A sequential display of the images produces linear motion parallax in the display. Further work enabled motion parallax to be combined with binocular parallax [NDT&E Int 29 (1996) 27] to produce dynamic binocular stereoscopic images. The perspective images may also be used for the extraction of three-dimensional coordinate information. The results produced by an experimental system are presented together with a theoretical discussion.

A study on the perspective images of Mt. Miwa from the standpoint of figure

１．はじめに（１）研究の背景と目的（２）既往研究からみた本研究の位置づけ（３）研究の方法２．三輪山とその形象について（１）三輪山について（２）著名眺望点と比較視点の抽出（３）三輪山の形象分析３．山頂部周辺の形象について４．地性線による形象について５．まとめ

A study on the perspective images of Mt.Miwa from the standpoint of figure

１.はじめに（１）研究の背景と目的（２）既往研究からみた本研究の位置づけ（３）研究の方法２．三輪山とその形象について（１）三輪山について（２）著名眺望点と比較視点の抽出（３）三輪山の形象分析３．山頂部周辺の形象について４．地性線による形象について５．まとめ

Pose determination of human faces by using vanishing points

A new method for estimating 3D-head pose from a monocular image is proposed in this paper. The approach employs general prior knowledge of face structure and the corresponding geometrical constraints provided by the location of vanishing point to determine pose of human faces. The connection of the two far-eye corners and the two neighboring-eye corners, respectively, form the eye-lines. Connecting the two far-mouth corners forms the mouth-line. The eye-lines and the mouth-line are assumed parallel in 3D space, and their vanishing point on the image plane can be used to infer 3D pose of the human face. Perspective projection imaging model is used and an accurate analytic solution of pose (position and orientation) of human face is deduced. The orientation of the facial plane can be obtained when the ratio of the lengths of the eye-line segment (far-eye corners) and the mouth-line segment (far-mouth corners) is known. Furthermore, if one of the two lengths is known, then the absolute positions of the feature corners can be located. The robustness analysis of the algorithm with synthetic data and the experimental results of real face images are enclosed.

3D Face Modeling from Perspective-Views and Contour-Based Generic-Model

Three-dimensional human head modeling is useful in video-conferencing or other virtual reality applications. However, manual construction of 3D models using CAD tools is often expensive and time-consuming. Here we present a robust and efficient method for the construction of a 3D human head model from perspective images viewing from different angles. In our system, a generic head model is first used, then three images of the head are required to adjust the deformable contours on the generic model to make it closer to the target head. Our contributions are as follows. Our system uses perspective images that are more realistic than orthographic projection approximations used in earlier works. Also, for shaping and positioning face organs, we present a method for estimating the camera focal length and the 3D coordinates of facial landmarks when the camera transformation is known. We also provide an alternative for the 3D coordinates estimation using epipolar geometry when the extrinsic parameters are absent. Our experiments demonstrate that our approach produces good and realistic results.

Recognition of polyhedral objects using triplets of projected spatial edges based on a single perspective image

A novel and intuitive mathematical formulation is proposed for the interpretation of the geometric relationships of a triple of spatial edges and their perspective projection forming image lines. No restriction is imposed on the configuration of the triple of spatial edges. An eighth-degree polynomial equation explicitly defined by the space angles between the corresponding three spatial edges in an object frame is derived. The crux of this representation is that the angular attributes of pairs of spatial edges are expressed in an object-independent coordinate system. An effective hypothesis generation scheme is proposed which can take advantage of the representation. In the proposed recognition framework, triples of connected spatial edges and trihedral vertices are employed as key features for model invocation, hypothesis generation and pose estimation. Extensive experiments are performed to verify the plausibility and robustness of the proposed recognition methods. In general, the success rate for identifying and localising polyhedral objects using the proposed recognition method is relatively high.