We present a feature extraction method for RGB-D data based on k-means clustering that builds on recent work by Coates et al. Using unsupervised learning methods we are able to automatically learn feature responses that combine all available information (color and depth) into one, concise representation. We show that depth information can substantially increase the recognition performance and t...

This paper considers the stability problem of Lur’e type descriptor systems (LDS) with sector and slope restricted nonlinearities. The concepts of global index one and strongly absolute stability are firstly introduced. Then by using S-procedure and matrix inequality approach, two sufficient conditions for LDS to be strongly absolutely stable are derived. It is shown that such conditions also g...

In this paper, a new method to calculate the similarity among images using Dominant Color Descriptor is discussed. Using Earth Mover’s Distance (EMD), better retrieval results can be obtained compared with those obtained from the original MPEG-7 reference software (XM) [1]. To further improve the retrieval accuracy, texture information from Edge Histogram Descriptor is added. In order to reduce...

Recognition of three dimensional (3D) objects in noisy and cluttered scenes is a challenging problem in 3D computer vision. One approach that has been successful in past research is the regional shape descriptor. In this paper, we introduce two new regional shape descriptors: 3D shape contexts and harmonic shape contexts. We evaluate the performance of these descriptors on the task of recognizi...

In this paper we propose a new numerically reliable computational approach to determine the inner-outer factorization of a rational transfer matrix G of a linear descriptor system. In contrast to existing computationally involved “one-shot” methods which require the solution of Riccati or generalized Riccati equations, the new approach relies on an efficient recursive zeros dislocation techniqu...

relies critically on the ability to find effective image features to represent the database images. The shape of an object is a fundamental image feature and belongs to one of the most important image features used in CBIR. In this article we propose a robust and effective shape feature known as the compound image descriptor (CID), which combines the Fourier transform (FT) magnitude and phase c...

Shapes and texture image recognition usage is an essential branch of pattern recognition. It is made up of techniques that aim at extracting information from images via human knowledge and works. Local Binary Pattern (LBP) ensures encoding global and local information and scaling invariance by introducing a look-up table to reflect the uniformity structure of an object. However, edge direction ...

The output-feedback control problem is solved for continuous-time, linear, retarded and neutral type systems. A delay-dependent solution is obtained in terms of linear matrix inequalities (LMIs) by using a descriptor model transformation of the system and by applying Park’s inequality for bounding cross terms. A state-feedback solution is derived for systems with polytopic parameter uncertainti...

Three main model transformations were used in the past for delay-dependent stability. Recently a new (descriptor) model transformation has been introduced. In the present paper, we compare methods under different transformations and show the advantages of the descriptor one. We obtain new delay-dependent stability conditions for systems with timevarying delays in terms of linear matrix inequali...

In this paper, we consider the regularization problem for the linear time-varying discrete-time periodic descriptor systems by derivative and proportional state feedback controls. Sufficient conditions are given under which derivative and proportional state feedback controls can be constructed so that the periodic closed-loop systems are regular and of index at most one. The construction proced...