Time-of-flight sensor and color camera calibration for multi-view acquisition

This paper presents a multi-view acquisition system using multi-modal sensors, composed of time-of-flight (ToF) range sensors and color cameras. Our system captures the multiple pairs of color images and depth maps at multiple viewing directions. In order to ensure the acceptable accuracy of measurements, we compensate errors in sensor measurement and calibrate multi-modal devices. Upon manifold experiments and extensive analysis, we identify the major sources of systematic error in sensor measurement and construct an error model for compensation. As a result, we provide a practical solution for the real-time error compensation of depth measurement. Moreover, we implement the calibration scheme for multi-modal devices, unifying the spatial coordinate for multi-modal sensors. The main contribution of this work is to present the thorough analysis of systematic error in sensor measurement and therefore provide a reliable methodology for robust error compensation. The proposed system offers a real-time multi-modal sensor calibration method and thereby is applicable for the 3D reconstruction of dynamic scenes.     

Dense versus Sparse Approaches for Estimating the Fundamental Matrix

There are two main strategies for solving correspondence problems in computer vision: sparse local feature based approaches and dense global energy based methods. While sparse feature based methods are often used for estimating the fundamental matrix by matching a small set of sophistically optimised interest points, dense energy based methods mark the state of the art in optical flow computation. The goal of our paper is to show that this separation into different application domains is unnecessary and can be bridged in a natural way. As a first contribution we present a new application of dense optical flow for estimating the fundamental matrix. Comparing our results with those obtained by feature based techniques we identify cases in which dense methods have advantages over sparse approaches. Motivated by these promising results we propose, as a second contribution, a new variational model that recovers the fundamental matrix and the optical flow simultaneously as the minimisers of a single energy functional. In experiments we show that our coupled approach is able to further improve the estimates of both the fundamental matrix and the optical flow. Our results prove that dense variational methods can be a serious alternative even in classical application domains of sparse feature based approaches.     

Eliminating the effect of freezing frames on user perceptive by using a time interleaving technique

Streaming video over a wireless network faces several challenges such as high packet error rates, bandwidth variations, and delays, which could have negative effects on the video streaming and the viewer will perceive a frozen picture for certain durations due to loss of frames. In this study, we propose a Time Interleaving Robust Streaming (TIRS) technique to significantly reduce the frozen video problem and provide a satisfactory quality for the mobile viewer. This is done by reordering the streaming video frames as groups of even and odd frames. The objective of streaming the video in this way is to avoid the losses of a sequence of neighbouring frames in case of a long sequence interruption. We evaluate our approach by using a user panel and mean opinion score (MOS) measurements; where the users observe three levels of frame losses. The results show that our technique significantly improves the smoothness of the video on the mobile device in the presence of frame losses, while the transmitted data are only increased by almost 9% (due to reduced time locality).     

Gender identity: The benefits of a self-schema approach.

Questions S. L. Bem's (see record 1983-21087-001) definition of a gender schema and argues that male and female sex-typed individuals do not have equivalent gender schemata. The high-androgynous individuals are the only ones for whom both masculinity and femininity are equally available and who might be properly termed "gender schematic." (6 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Electrophoretic deposition of nano-sized BaTiO3

In this study, a non-aqueous method in a simple one pot reaction process was employed to synthesize nano-sized BaTiO₃ particles and then electrophoretic deposition technique was employed for thin film coatings. In the first step of the preparation, metallic barium is directly dissolved in benzyl alcohol at slightly elevated temperatures. Then titanium isopropoxide was added following by a solvothermal treatment. At the end of the reaction, nearly spherical BaTiO₃ nanoparticles were obtained typically 5 nm in diameter. After establishing the stability of the BaTiO₃ suspension in ethanol, electrophoretic deposition process was performed without any additional operation. Alumina with platinum plating was used as substrate. To achieve the optimal process parameters, various voltages were applied by altering the cathode to anode distance as well as deposition time. High voltages application was possible without causing hydrolysis, because of the non-aqueous ethanol medium with higher surface charge of the nanoparticles. The deposited surface coatings were dried in air and sintered at various temperatures. SEM, EDX and XRD analysis were employed for the investigation of the coating.     

Lie point symmetries and conservation laws in microstretch and micromorphic elasticity

In this paper, following Noether’s theorem we investigate Lie point symmetries of linear theories of microstretch elasticity and micromorphic elasticity. We restrict our consideration to isotropic, compatible and homogeneous materials. Conservation and balance laws are derived, thereby extending results from micropolar elasticity.     

A pulsed neural network model of spectro-temporal receptive fields and population coding in auditory cortex

The existence of spectro-temporal receptive fields and evidence for population coding in auditory cortex motivate the development of such models, that explicitly operate in the time-frequency domain and are based on a pulsed neural network. In presenting such a model, a formal connection of the fields of Time Frequency Analysis and Pulsed Neural Networks is established. The resulting neural time-frequency signal representation is shown to be representable as a signal-dependent overcomplete dictionary. It is derived from neural population coding. Signal decomposition and filtering effects are presented, indicating obvious technical applications of the proposed model. This revised version was published online in June 2006 with corrections to the Cover Date.