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Surface metrologyand 3-D imaging with laser line scanners
Title
Surface metrologyand 3-D imaging with laser line scanners.
Creator
Kocak, D. M., Caimi, F. M., Harbor Branch Oceanographic Institute
Date Issued
1999
PURL
http://purl.flvc.org/fau/fd/FA00007314
Subject Headings
Scanning systems, Three-dimensional imaging, Lasers, Metrology, Geological mapping
Format
Document (PDF)
An approach to image compression using three-dimensional DCT
Title
An approach to image compression using three-dimensional DCT.
Creator
Furht, Borko, Li, Xiuqi
Date Issued
2003-09-24 - 2003-09-26
PURL
http://purl.flvc.org/fcla/dt/358419
Subject Headings
Image compression., Video compression., Three-dimensional display systems.
Format
Document (PDF)
POST PROCESSING METHODS FOR THREE DIMENSIONAL IMAGING LIDAR WITH MULTI-SCALE CHARACTERIZATION OF SUBSEA ORGANISMS
Title
POST PROCESSING METHODS FOR THREE DIMENSIONAL IMAGING LIDAR WITH MULTI-SCALE CHARACTERIZATION OF SUBSEA ORGANISMS.
Creator
McKenzie, Trevor Lee, Nayak, Aditya, Florida Atlantic University, Department of Ocean and Mechanical Engineering, College of Engineering and Computer Science
Abstract/Description
The thesis objective is to develop protocols that provide analysis and interpretation for data from a pulsed laser serial scanning lidar system for underwater imaging. The specific focus is remotely observing marine organisms in the centimeter size range in the poorly understood mesopelagic realm of the ocean. The Unobtrusive Multi-Static Lidar Imager (UMSLI) system captures an expansive volume scan field with differentiating imaging resolution per planar slice, allowing precise assignment of...
Show moreThe thesis objective is to develop protocols that provide analysis and interpretation for data from a pulsed laser serial scanning lidar system for underwater imaging. The specific focus is remotely observing marine organisms in the centimeter size range in the poorly understood mesopelagic realm of the ocean. The Unobtrusive Multi-Static Lidar Imager (UMSLI) system captures an expansive volume scan field with differentiating imaging resolution per planar slice, allowing precise assignment of location for organisms in the field of view. The multi-static highly collimated beams are recorded by a photo-multiplier tube receiver as a time lapse waveform of the returned energy flux, each waveform comprehensibly represents an image pixel in spatially and temporally. Complied lidar waveforms produce an array of returns which signify the magnitude of backscatter from varying sized particles across the observed volume. These volume scans are uniquely evaluated and transformed for each time bin through a processing method which extracts particle characteristics and statistics based on adaptive spatial and temporal techniques. The post processing method aims to greatly extend the capabilities of the lidar imaging system to extract particles. Results of the processing method are presented as particle counts and particle size distributions of the water columns during observed vertical migration periods. Methods are compared with other optical devices for validation, and results are interpreted to better understand the organism distribution in the mesopelagic and their behavior, with respect to diel vertical migrations.
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Date Issued
2019
PURL
http://purl.flvc.org/fau/fd/FA00013396
Subject Headings
Underwater imaging systems, Three-dimensional imaging--Methodology, Optical radar, Vertical distribution (Aquatic biology)
Format
Document (PDF)
Structure and motion estimation from image sequences
Title
Structure and motion estimation from image sequences.
Creator
Shieh, Jen-yu., Florida Atlantic University, Zhuang, Hanqi, Sudhakar, Raghavan, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
The objective of this dissertation is to develop effective algorithms for estimating the 3-D structure of a scene and its relative motion with respect to a camera or a pair of cameras from a sequence of images acquired by the cameras, under the assumption that the relative motion of the camera is small from one frame to another. This dissertation presents an approach of computing depth maps from an image sequence, which combines the direct depth estimation method with the optical flow based...
Show moreThe objective of this dissertation is to develop effective algorithms for estimating the 3-D structure of a scene and its relative motion with respect to a camera or a pair of cameras from a sequence of images acquired by the cameras, under the assumption that the relative motion of the camera is small from one frame to another. This dissertation presents an approach of computing depth maps from an image sequence, which combines the direct depth estimation method with the optical flow based method. More specifically, optical flow on and near moving edges are computed using a correlation technique. The optical flow information is then fused with the gradient information to estimate depth not only on moving edges but also in internal regions. Depth estimation is formulated as a discrete Kalman filter problem and is solved in three stages. In the prediction stage, the depth map estimated for the previous frame, together with knowledge of the camera motion, is used to predict the depth variance at each pixel in the current frame. In the estimation stage, a vector-version of Kalman filter formulation is adapted and simplified to refine the predicted depth map. The resulting estimation algorithm takes into account the information from the neighboring pixels, and thus is much more robust than the scalar-version Kalman filter implementation. In the smoothing stage, morphological filtering is applied to reduce the effect of measurement noise and fill in uncertain areas based on the error covariance information. Since the depth at each pixel is estimated locally, the algorithm presented in this paper can be implemented on a parallel computer. The performance of the presented method is assessed through simulation and experimental studies. A new approach for motion estimation from stereo image sequences is also proposed in this dissertation. First a stereo motion estimation model is derived using the direct dynamic motion estimation technique. The problem is then solved by applying a discrete Kalman filter that facilitates the use of a long stereo image sequence. Typically, major issues in such an estimation method are stereo matching, temporal matching, and noise sensitivity. In the proposed approach, owing to the use of temporal derivatives in the motion estimation model, temporal matching is not needed. The effort for stereo matching is kept to a minimum with a parallel binocular configuration. Noise smoothing is achieved by the use of a sufficiently large number of measurement points and a long sequence of stereo images. Both simulation and experimental studies have also been conducted to assess the effectiveness of the proposed approach.
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Date Issued
1992
PURL
http://purl.flvc.org/fcla/dt/12320
Subject Headings
Three-dimensional display systems, Imaging systems, Photography, Stereoscopic, Imaging transmission
Format
Document (PDF)
method to create three-dimensional facial image from two-dimensional facial data set
Title
A method to create three-dimensional facial image from two-dimensional facial data set.
Creator
Theerawong, Teerapat., Florida Atlantic University, Zhuang, Hanqi, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
A method to create 3D-face image using 2D-face images is the objective of this research. The 3D-face image is constructed using a set of 3D-face images of other persons available in a face database. The 3D-face image actually depicts a parameterized form in terms of depth and texture. This concept can be used to facilitate creating a 3D-face image from 2D database. For this purpose, a 3D-face database is first developed. When a 2D-face image is presented to the system, a 3D-face image that...
Show moreA method to create 3D-face image using 2D-face images is the objective of this research. The 3D-face image is constructed using a set of 3D-face images of other persons available in a face database. The 3D-face image actually depicts a parameterized form in terms of depth and texture. This concept can be used to facilitate creating a 3D-face image from 2D database. For this purpose, a 3D-face database is first developed. When a 2D-face image is presented to the system, a 3D-face image that starts with an average 3D-face image (derived from the 3D-face database) is projected onto the 2D-image plane, with necessary rotation, translation, scaling and interpolation. The projected image is then compared with the input image; and, an optimization algorithm is applied to minimize an error index by selecting 3D-depth and texture parameters. Hence, the projected image is derived. Once the algorithm converges, the resulting 3D-depth and the texture parameters can be employed to construct a 3D-face image of the subject photographed in the 2D-images. A merit of this method is that only the depth and texture parameters of the compared images are required to be stored in the database. Such data can be used either for the recreation of a 3D-image of the test subject or for any biometric authentication (based on 3D face recognition). Results from an experimental study presented in the thesis illustrate the effectiveness of the proposed approach, which has applications in biometric authentication and 3D computer graphics areas.
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Date Issued
2006
PURL
http://purl.flvc.org/fcla/dt/13407
Subject Headings
Image processing--Digital techniques, Computervision, Computer graphics, Three-dimensional display systems, Computer-aided design
Format
Document (PDF)