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Complexity of understanding a visual scene is the single biggest challenge in creating intelligent devices for visually impaired people. The requirement of real time operation makes it inevitable to design algorithms that obey the computing and memory limits of available hardware. We present a hierarchical scene understanding system implemented on a vision system chip. It is restricted to extract...
We study the problem of how to build a deep learning representation for 3D shape. Deep learning has shown to be very effective in variety of visual applications, such as image classification and object detection. However, it has not been successfully applied to 3D shape recognition. This is because 3D shape has complex structure in 3D space and there are limited number of 3D shapes for feature learning...
Caricature is a popular artistic media widely used for effective communications. The fascination of caricature lies in its expressive depiction of a person's prominent features, which is usually realized through the so called exaggeration technique. This paper proposes a new example based automatic caricature generation system supporting the exaggeration of visual appearance features. The system comprises...
In this paper, we try to hybrid projection twin support vector machine (PTSVM) and Extreme Learning Machine(ELM). The experiments shows that ELM generally out performs SVM/LS-SVM in various kinds of cases. PTELM tries to use ELM to overcome the shortness of PTSVM, which lacks of flexibility to change nonlinear kernel mapping for complex samples distribution regions. In order to overcome the shortness...
The curvature control problem for a class of hyper-redundant robot arms with continuum elements characterized by an elastic backbone system is analyzed. The main parameters of the arm shape as curvature and curvature gradient are estimated. The stability analysis and the resulting controllers are obtained using the concept of boundary geometric control and a weighted state control methods. The proposed...
Recent research in texture-based ear recognition also indicates that ear detection and texture-based ear recognition are robust against signal degradation and encoding artefacts. Based on these findings, we further investigate and compare the performance of texture descriptors for ear recognition and seek to explore possibilities to complement texture descriptors with depth information. On the basis...
A drive train system (DTS) powered by an ideal voltage source and driving a permanent magnet synchronous motor (PMSM) is discussed in this paper. A two-level, three-phase conventional inverter with no harmonic filters on both AC and DC sides is used as means of power conditioning. This DTS is modelled as a double oscillator according to a drive train in an electric vehicle. Various inverter modulation...
Regarding the palms recognition system studies, despite achieving a high success rate, hygiene problems in systems with contact and problems arising from changes in the alignment of the hand pose in non-contact ones have been encountered. To resolve these problems, 3D palmprint recognition systems have been developed, however these systems have not had the opportunity to spread due to expensive technologies...
A dynamic facial expression recognition method based on the auto-regressive (AR) models using combined features of both shape and texture features is proposed in this paper. The AR model is effective to model complicated facial motions. In this work, six AR models are first learned for six basic expressions based on the fusion of shape and texture features of the difference between the neutral image...
Nowadays, content-based image-retrieval techniques constitute powerful tools for archiving and mining of large remote sensing image databases. High spatial resolution images are complex and differ widely in their content, even in the same category. All images are more or less textured and structured. If the image to recognize is somewhat or very structured, a shape feature will be somewhat or very...
In this paper, a direct torque hysteresis controller (DTHC) driving a permanent magnet synchronous machine is discussed. A two-level, three-phase conventional inverter is used as means of power conversion. Advantages such as a low switching frequency as well as further opportunities of the DTHC are specified. The simulation results show a high degree of potential for the DTHC in future applications.
A drive train system (DTS) powered by an ideal voltage source and driving a permanent magnet synchronous motor (PMSM) is discussed in this paper. A two-level, three-phase conventional inverter with no harmonic filters on both AC and DC sides is used as means of power conditioning. This DTS is modelled as a double oscillator according to a simplified drive train in an electric vehicle. Commonly used...
In this paper, a novel method is proposed for the Traffic Sign Recognition (TSR) using the Principle Component Analysis (PCA) and the Multi-Layer Perceptrons (MLPs) network. In particular, the candidate signs are individually detected from two chroma components in the YCbCr space and then classified into three shape classes: circle, square, and triangle based on computing the rotated version correlations...
This paper investigates a control strategy for grid-connected wind energy conversion systems with doubly-fed induction generators, that employs a novel d-q hysteresis current regulator in the inner control loops. Although the current control is implemented in a rotating reference frame synchronous to the positive sequence space vector of the grid voltage, it can be used to generate negative sequence...
The authors propose a new parameter definition method and nail chip transformation method to superimpose nail chips onto dorsal-sided hand images with wrist rotation. Parameters for superimposing a nail chip on a fingernail are obtained using the center of gravity of the fingernail and the first and second principal component vector. A new transformation method was developed by including artificial...
This paper describes grasp point selection on an item of clothing randomly placed on a table. The input data for our proposed method is a range image captured from a fixed, 3D range camera. Hem elements are extracted from the data, and their relationships are characterized for both similarity measures and grasp point evaluation. Experiments using real images, targeting a piece of clothing, show the...
We present an approach for object class learning using a part-based shape categorization in RGB-augmented 3D point clouds captured from cluttered indoor scenes with a Kinect-like sensor. We propose an unsupervised hierarchical learning procedure which allows to symbolically classify shape parts by different specificity levels of detailedness of their surface-structural appearance. Further, a hierarchical...
Highly articulated robots have the potential to play a key role in minimally invasive surgeries by providing improved access to hard-to-reach anatomy. Estimating their shape inside the body and combining it with 3D preoperative scans of the anatomy enable the surgeon to visualize how the entire robot interacts with the internal organs. As the robot progresses inside the body, the position and orientation...
Learning to predict the effects of actions applied to pairs of objects is a difficult task that requires learning complex relations with sparse, incomplete and noisy information. Our Knowledge Propagation approach propagates affordance predictions by exploiting similarities among object properties, action parameters and resulting effects. The knowledge is propagated in a graph where a missing edge,...
We consider a coupled model of linear elasticity with Navier-Stokes equations. Two subdomains Ω1 and Ω2 are considered. In Ω1 there is a linear elasticity model. In Ω2 there is the fluid transport which is modeled by nonlinear Navier-Stokes equations. A propitiate interface conditions should be provided. We want to determine the shape and topological derivatives in Ω2.
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