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Articles 1 - 7 of 7
Full-Text Articles in Engineering
Fusion Of Imaging And Inertial Sensors For Navigation, Michael J. Veth
Fusion Of Imaging And Inertial Sensors For Navigation, Michael J. Veth
Theses and Dissertations
The motivation of this research is to address the limitations of satellite-based navigation by fusing imaging and inertial systems. The research begins by rigorously describing the imaging and navigation problem and developing practical models of the sensors, then presenting a transformation technique to detect features within an image. Given a set of features, a statistical feature projection technique is developed which utilizes inertial measurements to predict vectors in the feature space between images. This coupling of the imaging and inertial sensors at a deep level is then used to aid the statistical feature matching function. The feature matches and inertial …
Development Of A Cost Effective Mini Autonomous Underwater Vehicle, Chiu-Feng Lin, Chyuan-Yow Tseng
Development Of A Cost Effective Mini Autonomous Underwater Vehicle, Chiu-Feng Lin, Chyuan-Yow Tseng
Journal of Marine Science and Technology
This paper describes the development of a cost effective mini autonomous underwater vehicle. The mini size of the vehicle is achieved by extracting the control module hardware out from the vehicle vessel and by reducing the on-board sensors. The control of the vehicle is conducted by a base station wirelessly telecommunicating with the vehicle. Furthermore, the reduction of the sensors also reduces the cost of the vehicle. For the purpose, in the vehicle, a single sensor featuring a CCD camera is mounted at the front of the vehicle. The images taken by this CCD camera are used both for obstacle …
Imaging Breast Adipose And Fibroglandular Tissue Molecular Signatures By Using Hybrid Mri-Guided Near-Infrared Spectral Tomography, Ben Brooksby, Brian W. Pogue, Shudong Jiang, Hamid Dehghani, Subhadra Srinivasan, Christine Kogel, Tor D. Tosteson, John Weaver, Steven P. Poplack, Keith D. Paulsen
Imaging Breast Adipose And Fibroglandular Tissue Molecular Signatures By Using Hybrid Mri-Guided Near-Infrared Spectral Tomography, Ben Brooksby, Brian W. Pogue, Shudong Jiang, Hamid Dehghani, Subhadra Srinivasan, Christine Kogel, Tor D. Tosteson, John Weaver, Steven P. Poplack, Keith D. Paulsen
Dartmouth Scholarship
Magnetic resonance (MR)-guided near-infrared spectral tomography was developed and used to image adipose and fibroglandular breast tissue of 11 normal female subjects, recruited under an institutional review board-approved protocol. Images of hemoglobin, oxygen saturation, water fraction, and subcellular scattering were reconstructed and show that fibroglandular fractions of both blood and water are higher than in adipose tissue. Variation in adipose and fibroglandular tissue composition between individuals was not significantly different across the scattered and dense breast categories. Combined MR and near-infrared tomography provides fundamental molecular information about these tissue types with resolution governed by MR T1 images.
Fast Video Stabilization Algorithms, Mohammed A. Alharbi
Fast Video Stabilization Algorithms, Mohammed A. Alharbi
Theses and Dissertations
A fast and robust electronic video stabilization algorithm is presented in this thesis. It is based on a two-dimensional feature-based motion estimation technique. The method tracks a small set of features and estimates the movement of the camera between consecutive frames. It is used to characterize the motions accurately including camera rotations between two imaging instants. An affine motion model is utilized to determine the parameters of translation and rotation between images. The determined affine transformation is then exploited to compensate for the abrupt temporal discontinuities of input image sequences. Also, a frequency domain approach is developed to estimate translations …
Unconventional Optical Imaging Using A High Speed, Neural Network Based Smart Sensor, William W. Arrasmith
Unconventional Optical Imaging Using A High Speed, Neural Network Based Smart Sensor, William W. Arrasmith
Electrical Engineering and Computer Science Faculty Publications
The advancement of neural network methods and technologies is finding applications in many fields and disciplines of interest to the defense, intelligence, and homeland security communities. Rapidly reconfigurable sensors for real or near-real time signal or image processing can be used for multi-functional purposes such as image compression, target tracking, image fusion, edge detection, thresholding, pattern recognition, and atmospheric turbulence compensation to name a few. A neural network based smart sensor is described that can accomplish these tasks individually or in combination, in real-time or near real-time. As a computationally intensive example, the case of optical imaging through volume turbulence …
Image Processing Resource Allocation Methods For Multi-Target Tracking Of Dismounted Targets In Urban Environments, Jonathan P. Champion
Image Processing Resource Allocation Methods For Multi-Target Tracking Of Dismounted Targets In Urban Environments, Jonathan P. Champion
Theses and Dissertations
Dismounted targets can be tracked in urban environments with video sensors. Real-time systems are unable to process all of the imagery, demanding some method for prioritization of the processing resources. Furthermore, various segmentation algorithms exist within image processing, each algorithm possesses unique capabilities, and each algorithm has an associated computational cost. Additional complexity arises in the prioritization problem when targets become occluded (e.g., by a building) and when the targets are intermixed with other dismounted entities. This added complexity leads to the question "which portions of the scene warrant both low cost and high cost processing?" The approach presented in …
Hand Posture Recognition In Sign Language Using Shape Distributions, Eamonn Young, Gary Clynch
Hand Posture Recognition In Sign Language Using Shape Distributions, Eamonn Young, Gary Clynch
Conference Papers
A shape distribution is a histogram used to uniquely identify different shapes. The histogram is produced by taking random distances on the surface of a shape or object. Theoretically, each shape or object should produce a unique histogram, as the distribution of distances for each shape should be different. Shape distributions have recently been implemented in a number of object recognition areas. They are an attractive method as they are inherently simple, fast and generic. This paper presents the results of research undertaken on the application of shape distributions for the purpose of sign language recognition. There are four main …