Fast estimation of fundamental matrix based on stripe constraints

In order to improve the performance of estimating the fundamental matrix, a key problem arising in stereo vision, a novel method based on stripe constraints is presented. In contrast to traditional methods based on algebraic least-square algorithms, the proposed approach aims to minimize a cost function that is derived from the minimum radius of the Hough transform. In a structured-light system with a particular stripe code pattern, there are linear constraints that the points with the same code are on the same surface. Using the Hough transform, the pixels with the same code map to the Hough space, and the radius of the intersections can be defined as the evaluation function in the optimization progress. The global optimum solution of the fundamental matrix can be estimated using a Levenberg- Marquardt optimization iterative process based on the Hough transform radius. Results illustrate the validity of this algorithm, and prove that this method can obtain good performance with high efficiency.

Fabrication of virus-like particles with strip-pattern surface：A two-step self-assembly approach

Spherical nanostructures with striped patterns on the surfaces resembling the essential structures of natural virus particles were constructed through a two-step self-assembly approach of polystyrene-boligo（acrylic acid）（PS-b-oligo-AA） and poly（γ-benzyI L-glutamate）-b-poly（ethylene glycol）（PBLG-bPEG） copolymer mixtures in solution.On the basis of difference in hydrophilicity and self-assembly properties of the two copolymers,the two-step self-assembly process is realized.It was found that PS-boligo-AA copolymers formed spherical aggregates by adding a certain amount of water into polymer solutions in the first step.In the second step,two polymer solutions were mixed and water was further added,inducing the self-assembly of PBLG-b-PEG on the surfaces of PS-b-oligo-AA spheres to form striped patterns.In-depth study was conducted for the indispensable defects of striped patterns which are dislocations and ＋1/2 disclinations.The influencing factors such as the mixing ratio of two copolymers and the added water content in the first step on the morphology and defects of the striped patterns were investigated.This work not only presents an idea to interpret mechanism of the cooperative self-assembly behavior,but also provides an effective approach to construct virus-like particles and other complex structures with controllable morphology.

Particulate aggregation through a modulated annular one-dimensional acoustic field at resonant frequencies

The visualization and analysis of a novel acoustic-particulate system is the objective of this study. The system is composed of rice-husk fired smoke particulates (36.7 nm-840 μm) and one annular resonant circular-tube waveguide contrarily coupled with two sound sources. The collective interaction behavior process of smoke particulates in an inhomogeneous acoustic field is displayed during an experiment and a simulation. The result shows that the aggregation and fragmentation of particles under a change in resonant frequencies and sound pressure amplitude is extremely complex. This complex process consists of dynamically tuning the particle characteristics to attain stripes shaped like thin-films/umbrellas and clusters with volume-change/fragmentation. The balanced modulation of the acoustic radiation force and secondary radiation force to alter the particle characteristics (size and stack density) is verified to be the control mechanism of the particle system. The intermediate variable of the process control is the acoustic contrast factor (Φ) related to the physical characteristics of the growing particulates. The value plus-minus alternation of Φ results in different particulate processes. This study can enhance the application of aerodynamic acoustic-particulate-fluid systems for environment protection, energy fuel conversion, and industrial production.