In this paper, we present a method for fast and robust object recognition. As an example, the method is applied to traffic sign recognition from a forward-looking camera in a car. To facilitate and optimise the implementation of this algorithm on an embedded platform containing parallel hardware, we developed a voting scheme for constellations of visual words, i.e. clustered local features (SUR...

palmprint recognition is a new biometrics system based on physiological characteristics of the palmprint, which includes rich, stable, and unique features such as lines, points, and texture. texture is one of the most important features extracted from low resolution images. in this paper, a new local descriptor, local composition derivative pattern (lcdp) is proposed to extract smartly stronger...

This paper compares the performance of handgeometry recognition based on high-level features and on low-level features. The difference between highand lowlevel features is that the former are based on interpreting the biometric data, e.g. by locating a finger and measuring its dimensions, whereas the latter are not. The low-level features used here are landmarks on the contour of the hand. The ...

In many applications, different kinds of moments have been utilized to classify images and object shapes. Moments are important features used in recognition of different types of images. In this paper, three kinds of moments: Geometrical, Zernike and Legendre Moments have been evaluated for classifying 3D object images using Nearest Neighbor classifier. Experiments are conducted using ETH-80 da...

In this paper, we present an emotion recognition methodology that utilizes information extracted from body motion analysis to assess affective state during gameplay scenarios. A set of kinematic and geometrical features are extracted from joint-oriented skeleton tracking and are fed to a deep learning network classifier. In order to evaluate the performance of our methodology, we created a data...

The most facial emotion recognition methods use the geometrical features of face such as eye opening and mouth opening, which extraction of them is a hard and complicated task. But, in this paper, we propose to use the discriminant features simply extracted by nonparametric weighted feature extraction (NWFE). Moreover, to model the inherent uncertainties contained in the emotional features, we ...

Invariant features play a key role in object and pattern recognition studies. Features that are invariant to geometrical transformations offer succinct representations of underlying objects so that they can be reliably identified. In this paper, a family of novel invariant features is introduced based on Cartan’s theory of moving frames. These new features is called summation invariants. Compar...