waashk/dblp huggingface dataset:
surface models based on face hierarchies and dynamic control of the model lods. we present a new method of constructing hierarchical surface models which are represented by binary trees of faces. the models are useful both for hierarchical approximation of the surfaces and for efficient computation using the face-based hierarchy. our method creates at first a roughly approximated model and then generates the hierarchical models by iterative splitting faces. we also describe the method of dynamic control of levels of detail (lods) of the surface models. and we show the results of control of lods by a gaze point.
levels of detail control based on correlation analysis between surface position and direction. this paper presents a new lod control method using surface smoothness measure based on correlation analysis between surface position and direction. this control method renders smooth surface with less data. we also describe a new method of generating hierarchical data structures of face clusters.
motion tracking of cattle with a constrained deformable model. in this paper, we propose a method for monitoring the motion of cows by tracking the white patterns on them with constrained deformable models. as input for observation, we use image sequences of overhead views of cows taken by a camera installed on the ceiling of a breeding room. first, the 3d coordinates of the boundaries of the white patterns on the head, neck and torso parts respectively are registered. for each body part, the relationship betweenvariations of the patterns in appearance and the parameters specifying the movement are defined in advance from that part's movement characteristics. using deformable models which are constrained to be deformed based on these relations, the boundaries of the patterns are robustly tracked, producing as output the parameters specifying the movement of each part. preliminary experiments using actual image sequences have shown the practical usefulness of the proposed method.
a volumetric approach for the registration and integration of range images: towards interactive modeling systems. this paper presents a new approach for registering and integrating range images where these two processes are merged and performed in a common volumetric representation. the proposed approach allows both simultaneous and incremental registration where matching complexity is linear with respect to the number of images. this improvement leads to incremental modeling from range image acquisition to surface reconstruction. it is shown that the approach is tolerant to initial registration errors as well as to measurement errors while keeping the details of the initial range images. the paper describes the formalism of the approach. experimental results demonstrate performance advantages and tolerance to aforementioned types of errors for free form objects.
myocardial strain imaging with tagged mri. a 4-d b-spline model has been created to accurately capture the dynamic motion of the heart from tagged magnetic resonance imaging (mri) enabling displacement field reconstruction of myocardial deformation. the 4-d model is allowed to deform based on the location of the tag lines for all frames within the constraints of the model's spatio-temporal internal energy. from a displacement field, the corresponding long and short axis lagrangian strain maps are produced. motion fields from simulated data produced by a cardiac motion simulator are used to create corresponding strain images. in addition, strain images produced from porcine data with posterolateral myocardial in-farction are illustrated.
brain symmetry plane computation in mr images using inertia axes and optimization. detection of the best symmetry plane in 3d images can be treated as a registration problem between the original and the reflected images. the registration is performed in 3d space of parameters defining orientation and shift of reflection plane. we use the normalized l2 metric as the similarity measure between original and reflected images and investigate an algorithm for computation of the best symmetry plane. the algorithm computes first an initial position of the plane by analyzing principal inertia axes. we demonstrate on several mr brain images that the initial position is in the neighborhood of the global maximum. therefore the downhill simplex method is further used for the computation of the best symmetry plane. the proposed algorithm was tested on simulated and real mr brain images.
estimating rigid motions via the conformal model of euclidean space. estimating rigid motions from 3-d point correspondances and image projections is an important computer vision problem. we present a novel estimation algorithm using the recent conformal model of euclidean space. we derive an origin independent semi-closed form for the optimal transformation, solving it using an svd-based technique.
a unified information-theoretic approach to the correspondence problem in image registration. we consider the correspondence problem associated with the non-rigid registration of a group of images; in particular, the theoretical basis for the derivation of the objective function that defines the 'best' correspondence across a set of images. for intra-subject registration, there is an actual physical deformation process underlying the observed deformation, but for inter-subject registration, there is no such physical process, and hence no hypothetical process that generates the observed data. this leads to the conclusion that our construction should be based on the data alone. such a construction is possible using criteria derived from information theory. we show how many commonly used pairwise voxel-based similarity measures can be generated using these criteria, and discuss how this approach can be extended to give a unified theoretical basis for the generation of novel objective functions in the groupwise case, where both image discrepancy and image deformation terms should be included in a principled way.
ocr fonts revisited for camera-based character recognition. in order to realize accurate camera-based character recognition, machine-readable class information is embedded into each character image. specifically, each character image is printed with a pattern which comprises five stripes and the cross ratio derived from the pattern represents class information. since the cross ratio is a projective invariant, the class information is extracted correctly regardless of camera angle. the results of simulation experiments showed that recognition rates over 99% were obtained by the extracted cross ratio under heavy projective distortions.
using eigen-deformations in handwritten character recognition. deformations in handwritten characters have class-dependent tendencies. for example,characters of class "a" are often deformed by global slant transformation and never deformed to be similar to "r". in this paper, the extraction and the utilization of such tendencies called eigen-deformations are investigated for better performance of elastic matching basedrecognition systems. the eigen-deformations are extracted by the principal component analysis of actual deformations automatically collected by elastic matching. from experimental results it was shown that the extracted eigen-deformations represent typical deformations of each class. it was also shown that the recognition performance can be improved significantly by using the eigen-deformations in detecting overfitting, which often results in misrecognition.
active modeling of articulated objects with haptic vision. recently, there are growing needs for haptic exploration to estimate and extract physical object properties such as mass, friction, elasticity, function etc. in this paper, we propose a novel approach to active modeling of articulated objects with haptic vision. the method automatically extracts and describes both geometrical and physical properties of an articulated object, through the observation of interactions with active vision and "active touch" by a robot hand, using a ccd camera, range and force-feedback sensors. such models can provide users with reality-based interactions with the objects in virtual environments, to test and extract physical properties such as functions, parts motions and linking structures etc. experimental results on a paper punch and a pair of pliers were shown and these results were successfully used to construct a reality-based virtual environment simulator.
two-dimensional heteroscedastic linear discriminant analysis for age-group classification. this paper presents a novel lda algorithm named 2dhlda (2-dimensional heteroscedastic linear discriminant analysis). the proposed algorithms are applied on age-group classification using facial images under various lighting conditions. 2dhlda significantly overcomes the singularity problem, so-called 'small sample size' problem (s3 problem), and the original feature space is split into useful dimensions and nuisance dimensions to reduce the influence of different lighting conditions. a two-phased dimensional reduction step, namely 2dhlda+lda, is used in our experiment. our experimental results show that the new 2dhlda-based approach improves classification accuracy more than the conventional 1d and 2d-based approaches.
an efficient implementation technique of bidirectional matching for real-time trinocular stereo vision. bidirectional matching(bm) is an effective technique for area-based binocular stereo vision for maintaining one-toone correspondence, detecting half-occlusions and discarding false matches. this paper presents an extension of bm to trinocular stereo vision and proposes its memoryefficient implementation that maintains locality of memory access and thus enables the use of simd instruction sets of cpu for high time-performance. by using this scheme together with several other implementation techniques, 50fps throughput in generating disparity maps of approx. 320 × 240 sizes has been attained with ordinary pc workstations.
real-time cooperative multi-target tracking by communicating active vision agents. this paper presents a real-time cooperative multi-target tracking system. the system consists of a group of active vision agents (avas, in short) representing a logical model of a network-connected computer with an active camera. all avas track their target objects cooperatively by interacting dynamically with each other. as a result, the system as a whole can track multiple moving objects simultaneously under complicated dynamic situations in the real world. to implement real-time cooperation among avas, we designed a three-layered interaction architecture. in each layer, parallel processes mutually exchange a variety of information for effective cooperation. we employed the dynamic memory architecture to achieve real-time information exchange. experimental results demonstrated that avas track their target objects cooperatively in real-time while adaptively changing their roles.
extracting a gaze region with the history of view directions. we propose a method for extracting a gaze region from an observed image by analyzing human's view directions and image information. the view direction of the user, which is represented as a 2d gaze point in the observed image, is obtained by an eye-mark recorder at every image-capturing timing. all gaze points are translated to one of the images for extracting the gaze region based on the history of the view directions. the system divides all gaze points into several groups by comparing color information etc., and then generates several convex hulls as initial regions. each initial region is extended based on its color information and the spatial distribution of the gaze points. all regions are finally integrated and regarded as the gaze region.
probabilistic phase based sparse stereo. in this study, a multi-scale phase based sparse disparity algorithm and a probabilistic model for matching are proposed. the disparity algorithm and the probabilistic approach are verified on various stereo image pairs.
registration of range and color images using gradient constraints and range intensity images. this paper proposes a method for the registration of range and color (or intensity) images, based on the range intensity image that is simultaneously acquired with a range image. the gradient constraint between the range intensity image and the color image is introduced, and a linear equation for the registration parameters is derived, which combines displacement estimations for extrinsic and intrinsic parameters. by using the equation, precise automatic registration without explicit detection of correspondences is achieved. experimental results illustrate the proposed method.
a system to detect houses and residential street networks in multispectral satellite images. maps are vital tools for most government agencies and consumers. however, their manual generation and updating is tedious and time consuming. as a step toward automatic map generation, we introduce a novel system to detect houses and street networks in ikonos multispectral images. our system consists of four main blocks: multispectral analysis to detect cultural activity, segmentation of possible human activity regions, decomposition of segmented images, and graph theoretical algorithms to extract the street network and to detect houses over the decompositions. we tested our system on a large and diverse data set. our results indicate the usefulness of our system in detecting houses and street networks, hence generating automated maps.
a theoretical and experimental investigation of graph theoretical measures for land development in satellite imagery. cities are evolving and districts are changing their characteristics faster than ever before. although the evolution is slow in the central parts of most cities, it is typically fairly fast in outlying regions. they affect the public and private utility networks and maps become less reliable. as a result, emergency plans based on these maps may be ineffective. to assist experts, planners, policy makers, and civil defense organizations, we are developing automated techniques. in previous work, we considered discriminating rural and urban regions [classifying land development in high resolution satellite images using straight line statistics]. to automate the fine classification process, this paper introduces graph theoretical measures over grayscale images. these measures are monotonic with increasing structure (organization) in the image. thus, increased cultural activity and land development are indicated by increases in these measures - without explicit extraction of road networks, buildings, residences etc. we present a theoretical basis for the measures followed by extensive experimental results. we consider commercial ikonos data, which are metric images. our dataset is large and diverse, including sea and coastline, rural, forest, residential, industrial, and urban areas. on this data set we obtained promising results.
whole shape measurement system using a single camera and a cylindrical mirror. this paper proposes a three-dimensional measurement system with a simple structured system. the proposed system consists of a camera with a fish-eye lens and a cylinder whose inside is coated by a silver reflective layer. a target object is placed inside the cylinder and an image is captured by the camera from right above. the captured image includes sets of points that are observed from multiple viewpoints: one is observed directly, and the other is observed via the mirror. therefore, the whole shape of the object can be measured using stereo vision in a single shot. an actual experimental situation was simulated and the accuracy is evaluated. in addition, a prototype system was implemented and the shape of the real object was measured.
connected rotation-invariant size-shape granulometries. in this paper we describe a rotation-invariant multi-scale morphological method for texture analysis. compared with existing methods our method has three advantages. first, it can be implemented efficiently. furthermore, our method can be used for the computation of size and strict shape attributes, which we use for the computation of 2-d size-shape pattern spectra. finally, our method is rotation-invariant. although the latter can also be approximated by morphological methods by using structuring elements at different angles, this tends to be computationally intensive.
video synchronization based on co-occurrence of appearance changes in video sequences. this paper presents a method for synchronizing multiple cameras from only the images captured by the cameras, assuming that they are not connected to an external clock signal source. it is assumed that the cameras are stationary and take the images of the same scene from various viewpoints, in which there are moving objects such as human in motion. the method uses the appearance changes in an image sequence as a temporal feature and matches two or more sequences by evaluating the correlation among their temporal features. we show through several experiments that the method shows good performance of synchronization in spite of its simplicity. we also present a method for synchronization in sub-frame accuracy and also for adaptively selecting regions suitable for deriving the temporal features. the latter resolves the difficulty with the case where some objects appear in some of the cameras and do not in the rest, which could deteriorate accuracy of the synchronization.
a novel energy minimization criterion for color image segmentation. in this article, we present an unsupervised segmentation algorithm through a multiresolution approach which uses both color and edge information with a quadtree structure, through as well as an iterative minimization process of an energy function. the algorithm has been applied to fruit images in order to distinguish the different areas of the fruit surface in fruit quality assessment applications. due to the unsupervised nature of the method, it can adapt itself to the huge variability of colors and shapes of the regions in fruit inspection tasks.
clustering-based multispectral band selection using mutual information. this work presents the application of a novel technique on dimensionality reduction to deal with multispectral images. a distance based on mutual information is used to construct a hierarchical clustering structure. experimental results show that the method provides a very suitable subset of multispectral bands for pixel classification purposes.
view-based detection of 3-d interaction between hands and real objects. we propose a vision-based method to detect interactions between human hand(s) and real objects. since humans perform various kinds of tasks with their hands, detection of hand-object interactions is useful for building intelligent systems that understand and support human activities. we use a statistical color model to detect hand regions in input images. target objects are dynamically modeled based on their appearances by giving consideration to occlusions by the hand. the appearance model tracks the translation and relative rotation of target objects. this system is useful for recording, indexing and instructing object manipulations and/or hand-object interactions. experimental results show the effectiveness of our method.
audio segmentation and speaker localization in meeting videos. segmenting different individuals in a group meeting and their speech is an important first step for various tasks such as meeting transcription, automatic camera panning, multimedia retrieval and monologue detection. in this effort, given a meeting room video, we attempt to segment individual person's speech and localize them in the video, based on data from a single audio and video source. the segmentation method is driven by audio and enhanced by video cues. we used bayesian information criterion (bic) to segment the feature vector streams and graph spectral partitioning to cluster them. we compare our results with audio based segmentation method and our localization technique with the commonly used mutual information.
probabilistic shape-based image indexing and retrieval. in this paper we present a probabilistic framework for shape-based indexing and retrieval of images. in our framework shape-based features are extracted from each image and then a statistical model of the image is constructed using an effective determininstic method for gaussian mixture modeling. in this way, each image is finally represented as a mixture of gaussians and shape-based similarity between images is computed by measuring the distance between the corresponding mixture distributions. several distance measures are presented and experimentally compared. experimental results on the retrieval of logo images indicate that the method is very effective and exhibits robustness to the presence of various types of edge-related noise in the query image.
structural description of textile and tile pattern designs using image processing. cataloguing pattern and tiling designs using their geometrical features is an old research topic, whose main goal is the synthesis of new designs. but little effort have been made to approach the inverse problem, this is the analysis of a design using image processing techniques. in this paper a set of structural descriptors for automatically classifying designs of textile and tile fabric is proposed. graphic descriptors as parallelogram fundamental, design cluster, design symmetry axes etc.. are properly re-defined in a new framework that, using the theory of symmetry groups, tries to describe the structure of a pattern design. we describe the sequence of operations introduced for the analysis and extraction of these structural descriptors and the methodology used in each stage, devoting special attention to the techniques used in the image segmentation, object extraction, and clustering stages. experimental results with textile patrimony images and tile museum images are also included.
scan-to-xml: automatic generation of browsable technical documents. in this paper we experiment and validate an approach for the automatic generation of browsable technical documents. the application demonstrated in this work is restricted to cutaway diagrams with a particular visual representation. the global approach in which it is integrated is of a far more general interest, however. our principal aim is to automatically generate an xml description of a graphical document that will allow for further use of its content by establishing links within the document or with other documents, thus constructing a corpus of interconnected documents sharing zones of similar content or semantics.
a fast detector of line images acquired by an uncalibrated paracatadioptric camera. we propose a new method to simultaneously detect the images of lines acquired by an uncalibrated paracatadioptric camera and estimate its parameters. this method is very efficient thanks to our new linear formulation of the constraint for the paracatadioptric line images and to some proposed algorithmic improvements. the line images that are straight lines and circular arcs are detected similarly, after being projected to a virtual paraboloid. robust estimation methods are then used to find which detected line images are consistent with the best set of camera parameters. we provide experimental results that demonstrate the efficiency and robustness of the proposed method.