We present a method for frame coherent texturing and hatching of 3D models with a discrete set of colors. Our technique is inspired by various artistic styles that use a limited set of colors to convey surface shape and texture. In previous research discrete color shading was produced by modifying smooth shading with a threshold function. We extend this approach and specify threshold values wit...

A class of enhancement techniques is proposed for images in arbitrary dimension D. They are free from either space/frequency (scale) or grey references. There are two subclasses. One subclass is the chain: {Negative Laplace operator, Multiplication by Power (γ−1) of modulus-Laplace value, Inverse Negative Laplace operator} together with generalized versions. The generalization of the Negative L...

Edit propagation on images/videos has become more and more popular in recent years due to simple and intuitive interaction. It propagates sparse user edits to the whole data following the policy that nearby regions with similar appearances receive similar edits. While it gives a friendly editing mode, it often produces aliasing artifacts on edge pixels. In this paper, we present a simple algori...

Edit propagation on images/videos has become more and more popular in recent years due to simple and intuitive interaction. It propagates sparse user edits to the whole data following the policy that nearby regions with similar appearances receive similar edits. While it gives a friendly editing mode, it often produces aliasing artifacts on edge pixels. In this paper, we present a simple algori...

Agents learning to act in a partially observable domain may need to overcome the problem of perceptual aliasing – i.e., different states that appear similar but require different responses. This problem is exacerbated when the agent’s sensors are noisy, i.e., sensors may produce different observations in the same state. We show that many well-known reinforcement learning methods designed to dea...

In this paper, we propose a way to fuse the image-based localisation approach with the Monte-Carlo localisation approach. The method we propose does not suffer of the major limitation of the two separated methods: the need of a metric map of the environment for the Monte-Carlo localisation and the failure of the image-based approach in environments with spatial periodicity (perceptual aliasing)...

We develop a belief space planning (BSP) approach that advances the state of the art by incorporating reasoning about data association (DA) within planning, while considering additional sources of uncertainty. Existing BSP approaches typically assume data association is given and perfect, an assumption that can be harder to justify while operating, in presence of localization uncertainty, in am...

this paper  considersthe problem of  aliasing in information processing. the cubic spline method of interpolating the uniformly sampled signals and its effects on the autocorrelation estimation as well as the resulting spectral density function are studied by simulating random signals with known autocorrelation functions. hence, by comparison of aliased and alias-free cases, indications are ded...

The assumed scenario is transcription of a face-to-face conversation, such as in the financial industry when an agent and a customer talk over a desk with microphones placed between the speakers and then it is transcribed. From the automatic speech recognition (ASR) perspective, one of the speakers is the target speaker, and the other speaker is a directional noise source. When the number of mi...

For moderate and high speed values of the sea surface current, an aliasing phenomenon, due to an under-sampling in the time-domain, can strongly affect the reconstruction of the sea surface elevation derived from X-band radar images. Here, we propose a de-aliasing strategy that exploits the physical information provided by the dispersion law for gravity waves. In particular, we utilize simplify...