Recursive Recovery of Position and Orientation from Stereo Image Sequences without Three-Dimensional Structures

This paper introduces a reconfigurable closed-loop spatial mechanism that can be applied to repetitive motion tasks. The concept is to incorporate five pairs of non-circular gears into a six degree-of–freedom closed-loop spatial chain. The gear pairs are designed based on given mechanism parameters and a user defined motion specification of a coupler link of the mechanism. It is shown in the paper that planar gear pairs can be used if the spatial closed-loop chain is comprised of six pairs of parallel joint axes, i.e. the first joint axis is parallel to the second, the third is parallel to the fourth, ..., and the eleventh is parallel to the twelfth. This paper presents the synthesis of the gear pairs that satisfy a specified three-dimensional position and orientation need. Numerical approximations were used in the synthesis the non-circular gear pairs by introducing an auxiliary monotonic parameter associated to each end-effector position to parameterize the motion needs. The findings are supported by a computer animation. No previous known literature incorporates planar non-circular gears to fulfill spatial motion generation needs.

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A comparison of weighted LS methods with LS methods in 3-D motion estimation from stereo image sequences

Proceedings of IEEE Conference on Computer Vision and Pattern Recognition ◽

10.1109/cvpr.1993.340988 ◽

2002 ◽

Author(s):

S. Xuening ◽

M.E. Spetsakis

Keyword(s):

Motion Estimation ◽

Image Sequences ◽

Stereo Image

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A Video Super Resolution Algorithm Based on Wavelet Coefficient

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.610.425 ◽

2014 ◽

Vol 610 ◽

pp. 425-428

Author(s):

Wei Jian Liu ◽

Si Da Xiao ◽

Ruo He Yao

Keyword(s):

High Frequency ◽

Wavelet Coefficient ◽

Three Dimensional ◽

Super Resolution ◽

Structural Similarity ◽

Image Sequences ◽

Discrete Wavelet ◽

Resolution Image ◽

Resolution Algorithm ◽

Visual Results

In this paper, we propose a new super-resolution algorithm based on wavelet coefficient. The proposed algorithm uses discrete wavelet transform (DWT) to decompose the input low-resolution image sequences into four subband images, including LL, LH, HL, HH. Then the input images have been processed by the 3DSKR (Three Dimensional Steering Kernel Regression) super resolution (SR) algorithm, and the result replaces the LL subband image, while the three high-frequency subband images have been interpolated. Finally, combining all these images to generate a new high-resolution image by using inverse DWT. Proposed method has been verified on Calendar and Foliage by Matlab software platform. The peak signal-to-noise (PSNR), structural similarity (SSIM) and visual results are compared, and show that the computational complexity of the proposed algorithm decline by 30 percent compared with the existing algorithm to obtain the approximate results.

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The Optimum Cage Position and Orientation on the ALIF with Facet Screw Fixation: A Finite Element Analysis and the Taguchi Method

Journal of Mechanics ◽

10.1017/jmech.2011.25 ◽

2011 ◽

Vol 27 (3) ◽

pp. 309-320 ◽

Cited By ~ 1

Author(s):

C.-Y. Fan ◽

C.-K. Chao ◽

C.-C. Hsu ◽

K.-H. Chao

Keyword(s):

Finite Element ◽

Taguchi Method ◽

Screw Fixation ◽

Three Dimensional ◽

Element Model ◽

Lateral Position ◽

Element Analysis ◽

Control Factors ◽

Position And Orientation ◽

Noise Factors

ABSTRACTAnterior Lumbar Interbody Fusion (ALIF) has been widely used to treat internal disc degeneration. However, different cage positions and their orientations may affect the initial stability leading to different fusion results. The purpose of the present study is to investigate the optimum cage position and orientation for aiding an ALIF having a transfacet pedicle screw fixation (TFPS). A three-dimensional finite element model (ALIF with TFPS) has been developed to simulate the stability of the L4/L5 fusion segment under five different loading conditions. The Taguchi method was used to evaluate the optimized placement of the cages. Three control factors and two noise factors were included in the parameter design. The control factors included the anterior-posterior position, the medio-lateral position, and the convergent-divergent angle between the two cages. The compressive preload and the strengths of the cancellous bone were set as noise factors. From the results of the FEA and the Taguchi method, we suggest that the optimal cage positioning has a wide anterior placement, and a diverging angle between the two cages. The results show that the optimum cage position simultaneously contributes to a stronger support of the anterior column and lowers the risk of TFPS loosening.

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On the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences

International Journal of Biomedical Imaging ◽

10.1155/2011/137604 ◽

2011 ◽

Vol 2011 ◽

pp. 1-15 ◽

Cited By ~ 2

Author(s):

Jeyarajan Thiyagalingam ◽

Daniel Goodman ◽

Julia A. Schnabel ◽

Anne Trefethen ◽

Vicente Grau

Keyword(s):

Motion Estimation ◽

Real Time ◽

Three Dimensional ◽

Basic Research ◽

Estimation Algorithm ◽

Image Sequences ◽

Multicore Architectures ◽

Gpu Architectures ◽

Access Patterns ◽

Performance Gains

Images are ubiquitous in biomedical applications from basic research to clinical practice. With the rapid increase in resolution, dimensionality of the images and the need for real-time performance in many applications, computational requirements demand proper exploitation of multicore architectures. Towards this, GPU-specific implementations of image analysis algorithms are particularly promising. In this paper, we investigate the mapping of an enhanced motion estimation algorithm to novel GPU-specific architectures, the resulting challenges and benefits therein. Using a database of three-dimensional image sequences, we show that the mapping leads to substantial performance gains, up to a factor of 60, and can provide near-real-time experience. We also show how architectural peculiarities of these devices can be best exploited in the benefit of algorithms, most specifically for addressing the challenges related to their access patterns and different memory configurations. Finally, we evaluate the performance of the algorithm on three different GPU architectures and perform a comprehensive analysis of the results.

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