walkking's Top Recommendations

Abstract

This paper presents a new mutation strategy for the Metropolis light transport algorithm, which works in the unit cube of pseudo-random numbers instead of mutating in the path space. This transformation makes the integrand have lower variation and thus increases the acceptance probability of the mutated samples. Higher acceptance ratio, in turn, reduces the correlation of the samples, which increases the speed of convergence. We use both local mutations that choose a new random sample in... ...

Abstract

Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. A common constraint is that the labels should vary smoothly almost everywhere while preserving sharp discontinuities that may exist, e.g., at object boundaries. These tasks are naturally stated in terms of energy minimization. In this paper, we consider a wide class of energies with various smoothness constraints. Global minimization of these energy functions is NP-hard even in the simplest discontinuity-preserving case. Therefore, our focus is on ...

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Many problems in computer vision can be naturally phrased in terms of energy minimization. In the last few years researchers have developed a powerful class of energy minimization methods based on graph cuts. These techniques construct a specialized graph, such that the minimum cut on the graph also minimizes the energy. The minimum cut in turn is e#ciently computed by max flow algorithms. Such methods have been successfully applied to a number of important vision problems, including image... ...

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One of the most disastrous forms of collective human behaviour is the kind of crowd stampede induced by panic, often leading to fatalities as people are crushed or trampled. Sometimes this behaviour is triggered in life-threatening situations such as fires in crowded buildings1, 2; at other times, stampedes can arise during the rush for seats3, 4 or seemingly without cause. Although engineers are finding ways to alleviate the scale of such disasters, their frequency seems to be increasing with the number ...

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Large motion data sets often contain many variants of the same kind of motion, but without appropriate tools it is difficult to fully exploit this fact. This paper provides automated methods for identifying logically similar motions in a data set and using them to build a continuous and intuitively parameterized space of motions. To find logically similar motions that are numerically dissimilar, our search method employs a novel distance metric to find "close" motions and then uses them as intermediaries to ...

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In this paper we present a novel system for sketching the motion of a character. The process begins by sketching a character to be animated. An animated motion is then created for the character by drawing a continuous sequence of lines, arcs, and loops. These are parsed and mapped to a parameterized set of output motions that further reflect the location and timing of the input sketch. The current system supports a repertoire of 18 different types of motions in 2D ...

Abstract

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references. ...

Abstract

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references. ...

Abstract

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references. ...

Abstract

In this paper we present a novel method for creating realistic, controllable motion. Given a corpus of motion capture data, we automatically construct a directed graph called a motion graph that encapsulates connections among the database. The motion graph consists both of pieces of original motion and automatically generated transitions. Motion can be generated simply by building walks on the graph. We present a general framework for extracting particular graph walks that meet a user's specifications. We then show ...

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Using generic interpolation machinery based on solving Poisson equations, a variety of novel tools are introduced for seamless editing of image regions. The first set of tools permits the seamless importation of both opaque and transparent source image regions into a destination region. The second set is based on similar mathematical ideas and allows the user to modify the appearance of the image seamlessly, within a selected region. These changes can be arranged to affect the texture, the illumination, and the ...

Abstract

The aggregate motion of a flock of birds, a herd of land animals, or a school of fish is a beautiful and familiar part of the natural world. But this type of complex motion is rarely seen in computer animation. This paper explores an approach based on simulation as an alternative to scripting the paths of each bird individually. The simulated flock is an elaboration of a particle systems, with the simulated birds being the particles. The aggregate motion of the ...

Abstract

Random projection is a simple technique that has had a number of applications in algorithm design. In the context of machine learning, it can provide insight into questions such as “why is a learning problem easier if data is separable by a large margin?” and “in what sense is choosing a kernel much like choosing a set of features?” This talk is intended to provide an introduction to random projection and to survey some simple learning algorithms and other applications to ...

Abstract

This paper describes a template-matching-based system, called AdaMast, that detects onset times of the bass drum, snare drum, and hi-hat cymbals in polyphonic audio signals of popular songs. AdaMast uses the power spectrograms of the drum sounds as templates. However, there are two main problems in transcribing drum sounds in the presence of other sounds. The first problem is that actual drum-sound spectrograms cannot be prepared as templates beforehand for each song. The second problem is that ... ...

Abstract

Over the years, many discriminant analysis (DA) algorithms have been proposed for the study of high-dimensional data in a large variety of problems. Each of these algorithms is tuned to a specific type of data distribution (that which best models the problem at hand). Unfortunately, in most problems the form of each class pdf is a priori unknown, and the selection of the DA algorithm that best fits our data is done over trial-and-error. Ideally, one would like to have a ...

Abstract

A psychophysical investigation of timbre was undertaken with the intent of deriving quantitative results that could be useful in musical applications. Recordings of metal objects being struck with percussion mallets were rated by subjects on a unidimensional perceptual scale of perceived mallet hardness. Four acoustical parameters of the attack portion (first 325 ms) were defined and evaluated as predictors of perceived mallet hardness rating. To measure these parameters, a critical-band filter bank was employed. Two curves were extracted from the filter-bank ...

Abstract

Dominant theories of implicit learning assume that implicit learning merely involves the learning of chunks of adjacent elements in a sequence. In the experiments presented here, participants implicitly learned a nonlocal rule, thus suggesting that implicit learning can go beyond the learning of chunks. Participants were exposed to a set of musical tunes that were all generated using a diatonic inversion. In the subsequent test phase, participants either classified test tunes as obeying a rule (direct test) or rated their liking ...

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By formulating Helmholtz’s ideas about perception, in terms of modern-day theories, one arrives at a model of perceptual inference and learning that can explain a remarkable range of neurobiological facts: using constructs from statistical physics, the problems of inferring the causes of sensory input and learning the causal structure of their generation can be resolved using exactly the same principles. Furthermore, inference and learning can proceed in a biologically plausible fashion. The ensuing scheme rests on Empirical Bayes and hierarchical models ...

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10.1073/pnas.071525998 ...

Abstract

The auditory neural code must serve a wide range of auditory tasks that require great sensitivity in time and frequency and be effective over the diverse array of sounds present in natural acoustic environments. It has been suggested1, 2, 3, 4, 5 that sensory systems might have evolved highly efficient coding strategies to maximize the information conveyed to the brain while minimizing the required energy and neural resources. Here we show that, for natural sounds, the complete acoustic waveform can be ...

Abstract

Listening is an active process in which attentive focus on salient acoustic features in auditory tasks can influence receptive field properties of cortical neurons. Recent studies showing rapid task-related changes in neuronal spectrotemporal receptive fields (STRFs) in primary auditory cortex of the behaving ferret are reviewed in the context of current research on cortical plasticity. Ferrets were trained on spectral tasks, including tone detection and two-tone discrimination, and on temporal tasks, including gap detection and click-rate discrimination. STRF changes could be ...

Abstract

A comprehensive introduction to ICA for students and practitioners<br> Independent Component Analysis (ICA) is one of the most exciting new topics in fields such as neural networks, advanced statistics, and signal processing. This is the first book to provide a comprehensive introduction to this new technique complete with the fundamental mathematical background needed to understand and utilize it. It offers a general overview of the basics of ICA, important solutions and algorithms, and in-depth coverage of new applications in ...

Abstract

In this paper, we propose an effective approach to the nearly untouched problem, still photograph auto cropping, which is one of the important features to automatically enhance photographs. To obtain an optimal result, we first formulate auto cropping as an optimization problem by defining an energy function, which consists of three sub models: composition sub model, conservative sub model, and penalty sub model. Then, particle swarm optimization (PSO) is employed to obtain the optimal solution by maximizing the objective function. Experimental ...

Abstract

Summary  Computational methods for spline smoothing are studied in the context of the linear smoothing spline. Comparisons are made between two efficient methods for computing the estimator using band-limited basis functions and the Kalman filter. In particular, the Kalman filter approach is shown to be an efficient method for computing under the Kimeldorf-Wahba representation for the estimator. Run time comparisons are made between band-limited B-spline and Kalman filter based algorithms. ...

Abstract

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references. ...

Abstract

This paper proposes an image recognition method, which consists of two steps: features extraction based on wavelet transform and image recognition using artificial neural networks. More specifically, wavelet transform is used to decompose the original image into different frequency sub-bands, then a set of features are extracted from the wavelet coefficients. The feature set as input fed into neural network for recognition. The experimental results confirmed effectiveness of the proposed approach. ...

Abstract

Accurate image segmentation is important for many image, video and computer vision applications. Over the last few decades, many image segmentation methods have been proposed. However, the results of these segmentation methods are usually evaluated only visually, qualitatively, or indirectly by the effectiveness of the segmentation on the subsequent processing steps. Such methods are either subjective or tied to particular applications. They do not judge the performance of a segmentation method objectively, and cannot be used as a means to compare ...

Abstract

Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be ...

Abstract

The problem of efficient, interactive foreground/background segmentation in still images is of great practical importance in image editing. Classical image segmentation tools use either texture (colour) information, e.g. Magic Wand, or edge (contrast) information, e.g. Intelligent Scissors. Recently, an approach based on optimization by graph-cut has been developed which successfully combines both types of information. In this paper we extend the graph-cut approach in three respects. First, we have developed a more powerful, iterative version of the optimisation. Secondly, the power ...

Abstract

We present a graph cuts-based image segmentation technique that incorporates an elliptical shape prior. Inclusion of this shape constraint restricts the solution space of the segmentation result, increasing robustness to misleading information that results from noise, weak boundaries, and clutter. We argue that combining a shape prior with a graph cuts method suggests an iterative approach that updates an intermediate result to the desired solution. We first present the details of our method and then demonstrate its effectiveness in segmenting vessels ...

Abstract

Graph cut image segmentation with intensity information alone is prone to fail for objects with weak edges, in clutter, or under occlusion. Existing methods to incorporate shape are often too restrictive for highly varied shapes, use a single fixed shape which may be prone to misalignment, or are computationally intensive. In this note we show how highly variable nonlinear shape priors learned from training sets can be added to existing iterative graph cut methods for accurate and efficient segmentation of such ...

Abstract

We present a novel approach to image segmentation using iterated Graph Cuts based on multi-scale smoothing. We compute the prior probability obtained by the likelihood from a color histogram and a distance transform using the segmentation results from graph cuts in the previous process, and set the probability as the t-link of the graph for the next process. The proposed method can segment the regions of an object with a stepwise process from global to local segmentation by iterating the graph-cuts ...

Abstract

This paper proposes an approach to image segmentation using iterated graph cuts based on local texture features of wavelet coefficient. Using multiresolution analysis based on Haar wavelet, low-frequency range (smoothed image) is used for n-link and high-frequency range (local texture features) is used for t-link along with color histogram. The proposed method can segment the object region with noisy edges and colors similar to the background, but heavy texture change. Experimental results illustrate the validity of our method. ...

Abstract

In recent years, segmentation with graph cuts is increasingly used for a variety of applications, such as photo/video editing, medical image processing, etc. One of the most common applications of graph cut segmentation is extracting an object of interest from its background. If there is any knowledge about the object shape (i.e. a shape prior), incorporating this knowledge helps to achieve a more robust segmentation. In this paper, we show how to implement a star shape prior into graph ...

Abstract

In this paper, a fast automatic segmentation algorithm based on AdaBoost learning and iterative Graph-Cuts are shown. AdaBoost learning method is introduced for automatically finding the approximate location of certain object. Then an iterative Graph-Cuts method is used to model the segmentation problem. We call our algorithm as AdaBoost Aggregation Iterative Graph-Cuts (AAIGC). Compared to previous methods based on Graph-Cuts, our method is automatic. Once certain object is trained, our algorithm can cut it out from an image containing the certain ...

Abstract

An automatic segmentation algorithm based on AdaBoost learning and iterative Graph-Cuts are shown in this paper. In order to find the approximate location of the object, AdaBoost learning method is used to automatically find the object by the trained classifier. Some details on AdaBoost are described. Then the nodes aggregation method and the iterative Graph-Cuts method are used to model the automatic segmentation problem. Compared to previous methods based on Graph-Cuts, our method is automatic. This is a main feature of ...

Abstract

Most existing techniques of foreground extracting work only in interactive mode. This paper introduces a novel algorithm of automatic foreground extraction for special object, and verifies its effectiveness with head shoulder images. The main contribution of our idea is to make the most use of the prior knowledge to constrain the processing of foreground extraction. For human head shoulder images, we first detect face and a few facial features, which helps to estimate an approximate mask covering the interesting region. The ...

Abstract

We describe a means to automatically and efficiently isolate the outer surface of the entire heart in computer tomography (CT) cardiac scans. Isolating the entire heart allows the coronary vessels on the surface of the heart to be easily visualized despite the proximity of surrounding organs such as the ribs and pulmonary blood vessels. Numerous techniques have been described for segmenting the left ventricle of the heart in images from various types of medical scanners but rarely has the entire heart ...

Abstract

This work presents a landmark detection system for the walking robot operating in unknown unstructured outdoor environments. Most landmark detection approaches are not adequate for this application, since they rely on either structured information or a priori knowledge about the landmarks. Instead, the proposed system makes use of visual saliency concepts stemming from studies of animal and human perception. Thus, biologically inspired opponent features (in color and orientation) are searched for at different resolution levels. The implementation does not try to ...

Abstract

Image adaptation, one of the essential problems in adaptive content delivery for universal access, has been actively explored for some time. Most existing approaches have focused on generic adaptation with a view to saving file size under constraints in client environment and have hardly paid attention to user perceptions of the adapted result. Meanwhile, the major limitation on the user’s delivery context is moving away from data volume (or time-to-wait) to screen size because of the galloping development of hardware technologies. ...

Abstract

Pictures have become increasingly common and popular in mobile communication. However, due to the limitation of mobile devices, there is a need to develop new technologies to facilitate the browsing of pictures on the small screen. MobiPicture is a prototype system which includes a set of novel features to aid or automate a set of common image browsing tasks such as the thumbnail view, set-as-background, zooming and scrolling. ...