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Shape matching is a very important issue and challenging task in computer vision. In this paper, the problem of finding a matching between two shapes is addressed by establishing correspondences between two their skeleton graphs based on random walk framework. We first propose a novel skeleton graph model in which nodes represent end-nodes of skeleton while edges describe relations between two end-nodes...
A conventional approach to image analysis is to perform separately feature extraction at a low level (such as edge detection) and follow this with high level feature extraction to determine structure (e.g. by collecting edge points using the Hough transform. The original image Ray Transform (IRT) demonstrated capability to extract structures at a low level. Here we extend the IRT to add shape specificity...
Gender classification of depth images is a challenging problem, most research work attempted to use shape information to solve this problem in the past literature. In this work, we propose a new fusion scheme for gender classification using both texture and shape features. A new ensemble scheme is advocated to combine texture and shape feature at the feature level. To evaluate the performance of our...
In this paper, we present two methods to improve the performance of landmark detection algorithms that are designed to detect individual landmarks. We focus on the landmark configuration module that takes the output of the individual landmark detectors and searches for a configuration of optimal landmark locations based on appropriate shape constraints. We design two configuration search approaches:...
A 3D morphable face model represents the complex shape and appearance structure of faces as a compact representation in a vector space. Such a model has proven extremely useful in various fields such as face recognition, facial expression synthesis, face animation, as well as in the perceptual and cognitive sciences. One of the most important steps in creating a 3D morphable model is to establish...
In this paper, a new snake external force is proposed as the gradient of the image local energy diffusion potential. The local energy is computed using a bank of orthogonal log Gabor filters. The proposed Local Energy Diffusion Field (LEDF) is computed by energy diffusion Partial Differential Equation (PDE). The results of the LEDF snake were compared with the GVF snake in terms of capture range,...
Abnormal behavior detection has recently gained growing interest from computer vision researchers. In this paper, the gait-analysis-based abnormal detection is proposed for walking scenes, where gaits of people are analyzed in all kinds of situations and the gait data are utilized to construct the basic gait model. Walking people in the crowd are tracked and their activities silhouettes are abstracted...
Mobility in large touristic cities (such as Rome and Venice), where needs of citizen and tourists are different(and sometimes even conflicting), is a very relevant problem and info mobility is thus increasingly important. Since active technologies, requiring the passengers to wear some devices(e.g., RFID devices) are not commonly available and cannot be enforced on citizens and tourists, a complete...
With the proliferation of digital cameras and automatic acquisition systems, scientists can acquire vast numbers of images for quantitative analysis. However, much image analysis is conducted manually, which is both time consuming and prone to error. As a result, valuable scientific data from many domains sit dormant in image libraries awaiting annotation. This work addresses one such domain: coral...
Shape from shading is a classical inverse problem in computer vision. We introduce a novel mathematical formulation for calculating local surface shape based on covariant derivatives, rather than the customary integral minimization or P.D.E approaches. Motivated by neurobiology, we introduce the shading flow field (the tangent map to the image isophotes) between the image and the surface levels. Just...
In the field of computer vision, pyramid matching by minimization has gained increasing popularity. This paper points out and discusses an inherent anomaly in pyramid matching by minimization that can affect the performance of classification approaches based on this type of matching. As a solution, a new multiresolution measure, called Manhattan-Pyramid Distance (MPD), is proposed. Systematic evaluations...
Finding correspondences between two 3D shapes is common both in computer vision and computer graphics. In this paper, we propose a general framework that shows how to build correspondences by utilizing the isometric property. We show that the problem of finding such correspondences can be reduced to the problem of spectral assignment, which can be solved by finding the principal eigenvector of the...
Intelligent vehicle lighting systems aim at automatically regulating the headlights' beam to illuminate as much of the road ahead as possible while avoiding dazzling other drivers. A key component of such a system is computer vision software that is able to distinguish blobs due to vehicles' headlights and rear lights from those due to road lamps and reflective elements such as poles and traffic signs...
This paper proposes a meta-heuristic image processing application for mobile robot navigation. It classifies figures that are drawn on a wall by hand with a laser pointer. Image processing technique extracts optical flow of the laser beam trail, which represents vectors along edges of shapes. Genetic programming learns geometric characteristics of laser trail shapes and creates classification algorithm...
We propose a novel shape descriptor-Included Angle Histogram -for correspondence recovery of graphic vertex and shape-based object recognition. After detecting points local maximal curvature with and the center point of the contour, we construct vectors from the center point to the curvature points. Consequently the point descriptor can be obtained through computing the histograms of included-angles...
A great deal of descriptors for region matching have been proposed in last years. However, an extra step, fitting the irregular regions into fixed shapes, must be implemented in advance when constructing these descriptors on irregular regions. This fitting step can cause great errors, and thus will result in poor matching. Base on inner product and exterior product, this paper develops a method for...
Enlarging or reducing the template size by adding new parts, or removing parts of the template, according to their suitability for tracking, requires the ability to deal with the variation of the template size. For instance, real-time template tracking using linear predictors, although fast and reliable, requires using templates of fixed size and does not allow on-line modification of the predictor...
Image encoding using interest points is a common technique in computer vision. In this paper we present a scale and rotation invariant shape centered interest point (SCIP) detector. By means of detecting singularities in Gradient Vector Flow (GVF) fields we find points of high symmetry in the image. Due to the nature of the underlying GVF field we can employ our features to group together edge-based...
We propose to evaluate our sparsity driven people localization framework on crowded complex scenes. The problem is recast as a linear inverse problem. It relies on deducing an occupancy vector, i.e. the discretized occupancy of people on the ground, from the noisy binary silhouettes observed as foreground pixels in each camera. This inverse problem is regularized by imposing a sparse occupancy vector,...
Unsupervised over-segmentation of an image into super-pixels is a common preprocessing step for image parsing algorithms. Superpixels are used as both regions of support for feature vectors and as a starting point for the final segmentation. In this paper we investigate incorporating a priori information into superpixel segmentations. We learn a probabilistic model that describes the spatial density...
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