One of the most demanding challenges for real-time shadow algorithms is their application to large-scale, polygon-rich and dynamic environments. In this paper, we discuss the major problems encountered in applying shadow maps to such an environment and provide practical and robust solutions to the appearing problems. We tackle projection aliasing with the aid of an eye space blur. We compare th...

To improve image quality in computer graphics, antialiasing techniques such as supersampling and multisampling are used. We explore a family of inexpensive sampling schemes that cost as little as 1.25 samples per pixel and up to 2.0 samples per pixel. By placing sample points in the corners or on the edges of the pixels, sharing can occur between pixels, and this makes it possible to create ine...

A new approach to the design of M-channel pseudoquadrature-mirror-filter (QMF) banks is presented. In this approach, the prototype filter is obtained as a spectral factor of a 2Mth band filter. This completely eliminates the need for optimization whereas in conventional pseudo-QMF designs, the main computational effort is in optimization of the prototype. As in the conventional approach, the al...

SIFT is one of the most popular algorithms to extract points of interest from images. It is a scale+rotation invariant method. As a consequence, if one compares points of interest between two images subject to a large viewpoint change, then only a few, if any, common points will be retrieved. This may lead subsequent algorithms to failure, especially when considering structure and motion or obj...

Semantic Role Labeling (SRL) is the task of identifying the predicate-argument structure in sentences with semantic frame and role labels. For the English language, the Proposition Bank provides both a lexicon of all possible semantic frames and large amounts of labeled training data. In order to expand SRL beyond English, previous work investigated automatic approaches based on parallel corpor...

Uniformly-spaced apertures or subapertures of large, densely-sampled, discrete linear receiver arrays are often used in remote sensing to increase the signal-to-noise ratio (SNR) by coherent beamforming that reduces noise coming from directions outside the signal beam. To avoid spatial aliasing or the presence of grating lobes in real spatial directions, the uniformly-spaced array inter-element...

We have proposed a novel process flow for translational-invariant (TI) and ultrahigh-resolution (UHR) bistatic synthetic aperture radar (BSAR) operations, wherein UHR BSAR image is obtained via coherent integration of sub-aperture images, its two-dimensional (2D) coordinates are then interpreted. The main contributions the method as follows. First, to address additional aliasing TI spectrum aft...

This paper presents a method of vision-based reinforcement learning by which a robot learns to shoot a ball into a goal, and discusses several issues in applying the reinforcement learning method to a real robot with vision sensor. First, a \state-action deviation" problem is found as a form of perceptual aliasing in constructing the state and action spaces that re ect the outputs from physical...

Fig. 1. Our paper gives a novel compiler framework for smoothing out programs in an approximate manner. Here we show how our smoothing framework can be applied to bandlimiting (antialiasing) procedural shader programs. In (a) is the ground truth result for a brick shader, estimated by using 1000 samples; (b) is the aliased result due to naively evaluating the original shader program; (c) is our...

We describe two quite different methods for associating action parameters to visual percepts. Our RLVC algorithm performs reinforcement learning directly on the visual input space. To make this very large space manageable, RLVC interleaves the reinforcement learner with a supervised classification algorithm that seeks to split perceptual states so as to reduce perceptual aliasing. This results ...