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Developing traffic signal control methods is considered as the most important way to improve the traffic efficiency of modern roundabouts. This paper applies a traffic signal controller with two fuzzy layers for signalizing roundabouts. The outer layer of the controller computes urgency degrees of all the phase subsets and then activates the most urgent subset. This mechanism helps to instantly respond...
State-of-the-art methods for human detection and pose estimation require many training samples for best performance. While large, manually collected datasets exist, the captured variations w.r.t. appearance, shape and pose are often uncontrolled thus limiting the overall performance. In order to overcome this limitation we propose a new technique to extend an existing training set that allows to explicitly...
We describe a system that builds quantitative structural descriptions of spiral galaxies. This enables translation of sky survey images into data needed to help address fundamental astrophysical questions such as the origin of spiral structure — a phenomenon that has eluded full theoretical description despite 150 years of study. The difficulty of automated measurement is underscored by the fact that,...
While the detection of the interesting regions in images has been extensively studied, relatively few papers have addressed surfaces. This paper proposes an algorithm for detecting the regions of interest of surfaces. It looks for regions that are distinct both locally and globally and accounts for the distance to the foci of attention. Many applications can utilize these regions. In this paper we...
In this paper, we propose a very efficient novel parametric model to describe the surface and structure of the human tongue and a corresponding mathematical model for performing 3D tongue animation. A skeletal chain of virtual bones is automatically generated depending on the geometric features of the 3D object, allowing each tongue segment to be easily manipulated by its corresponding parameters,...
Pedestrian detection from images is an important and yet challenging task. The conventional methods usually identify human figures using image features inside the local regions. In this paper we present that, besides the local features, context cues in the neighborhood provide important constraints that are not yet well utilized. We propose a framework to incorporate the context constraints for detection...
The fast radial symmetry (FRS) transform has been very popular for detecting interest points based on local radial symmetry1. Although FRS delivers good performance at a relatively low computational cost and is very well suited for a variety of real-time computer vision applications, it is not invariant to perspective distortions. Moreover, even perfectly (radially) symmetric visual patterns in the...
We present a machine learning framework that automatically generates a model set of landmarks for some class of registered 3D objects: here we use human faces. The aim is to replace heuristically-designed landmark models by something that is learned from training data. The value of this automatically generated model is an expected improvement in robustness and precision of learning-based 3D landmarking...
Gap Completion is a key step in the process of linking of edges into contours towards generating meaningful boundaries. The likelihood of completing a gap between two edges has been approached either indirectly through studying optimal completion contours such as Elastica and Euler Spiral, or through the statistics of co-occurrence. These studies do not address the issue of finding appropriate candidates...
This paper develops a new constructing approach of an appropriate membership function to integrate a given probability density function and fuzzy Shannon entropy extending the statistical theory into the heuristic method based on the human cognitive behavior and subjectivity. The proposed approach is formulated as a more general mathematical programming problem than previous approaches due to using...
Markerless 3D human pose detection from a single image is a severely underconstrained problem because different 3D poses can have similar image projections. In order to handle this ambiguity, current approaches rely on prior shape models that can only be correctly adjusted if 2D image features are accurately detected. Unfortunately, although current 2D part detector algorithms have shown promising...
We introduce global regularities in the 2.5D building modeling problem, to reflect the orientation and placement similarities between planar elements in building structures. Given a 2.5D point cloud scan, we present an automatic approach that simultaneously detects locally fitted plane primitives and global regularities. While global regularities are extracted by analyzing the plane primitives, they...
Currently, most authentication system requires users to answer the CAPTCHA (Completely Automated Public Turing Test to Tell Computer and Human Apart) before gaining the system access. CAPTCHA is a standard security technology for distinguish between human and computer program automatically. The problem of using CAPTCHA is the difficulty of reading the text-based presentation, or interpreting the image-based...
The direct perception of actions allows a robot to predict the afforded actions of observed objects. In this paper, we present a non-parametric approach to representing the affordance-bearing subparts of objects. This representation forms the basis of a kernel function for computing the similarity between different subparts. Using this kernel function, together with motor primitive actions, the robot...
This paper presents a probabilistic framework combining heterogeneous, uncertain, information such as object observations, shape, size, appearance of rooms and human input for semantic mapping. It abstracts multi-modal sensory information and integrates it with conceptual common-sense knowledge in a fully probabilistic fashion. It relies on the concept of spatial properties which make the semantic...
Morphology of bones, teeth, and some particular structures are widely used for categorizing species and studying their evolution. In this paper, we used groupwise registration to provide a representative image from the set of the image samples that represents its typical morphology. We also provided perturbation map which indicates the deviation of each point through the ensemble. These images support...
What encourages people to refer to a robot as if it was a living being? Is it because of the robot's humanoid or animal-like shape, its movements or rather the kind of interaction it enables? We aim to investigate robots' characteristics that lead people to anthropomorphize it by comparing different kinds of robotic devices and contrasting it to an interactive technology. We addressed this question...
Extracting and labeling sulcal curves on the human cerebral cortex is important for many neuroscience studies, however manually annotating the sulcal curves is a time-consuming task. In this paper, we present an automatic sulcal curve extraction method by registering a set of dense landmark points representing the sulcal curves to the subject cortical surface. A Markov random field is used to model...
We present a shape-space approach for analyzing genetic influences on the shapes of the sulcal folding patterns on the cortex. Sulci are represented as continuously parameterized functions in a shape space, and shape differences between sulci are obtained via geodesics between them. The resulting statistical shape analysis framework is used not only to construct populations averages, but also used...
This paper presents the result of a recent large-scale subjective study of image retargeting quality on a collection of images generated by several representative image retargeting methods. Owning to many approaches to image retargeting that are developed, there is a need for a diverse independent public database of the retargeted images and the corresponding subjective scores that is freely available...
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