Application of direct linear transform for calibration of miniature computed tomography

2012 ◽  
Author(s):  
W. Pannao ◽  
C. Pintavirooj
Keyword(s):  
Computed Tomography ◽  
Linear Transform ◽  
Direct Linear Transform

scholarly journals Hybrid Facial Features with Application in Person Identification

2020 ◽  
Author(s):  
Boonchana Purahong ◽  
Vanvisa Chutchavong ◽  
Hisayuki Aoyama ◽  
Chuchart Pintavirooj
Keyword(s):  
Three Dimensional ◽  
Facial Feature ◽  
Geometric Transformation ◽  
Facial Features ◽  
Facial Image ◽  
Edge Image ◽  
A Value ◽  
Linear Transform ◽  
Direct Linear Transform ◽  
Facial Identification

This paper presents the hybrid facial feature with identification and verification based on facial images. A query facial image had been taken under different conditions of the facial image of the same person (as the query). The query facial image database was constructed. We have used the technique of three-dimensional (3D) Dlib facial landmarks using a direct linear transform technique. A set of absolute affine invariance had been constructed from a series of the 3D landmark quadruplets, which make the facial identification robust to affine geometric transformation. These 3D facial features serve as a coarse feature depending on each individual facial structure. The construct of the 2D detail features represents the edge facial image confined between the 2D Dlib landmarks. The similarity of the 2D feature is achieved by aligning the 2D query edge image against that of the reference edge image. The geometric transformation matrix is estimated from the 2D Dlib landmarks, where correspondence is well established. An identification/verification cost function using a combination of local 2D facial features and global 3D facial features is utilized to verify and identify a query facial image against a candidate facial image(s). The performance of the algorithm yielding an area of 99.97% perfect classification is represented as a value under the receiver operating characteristic (ROC) curve.  

scholarly journals Swimmer’s Head Detection Based on a Contrario and Scaled Composite JTC Approaches

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
D. Benarab ◽  
T. Napoléon ◽  
A. Alfalou ◽  
A. Verney ◽  
P. Hellard
Keyword(s):  
Moving Objects ◽  
Tracking System ◽  
Random Noise ◽  
Region Of Interest ◽  
Reference Image ◽  
Correlation Technique ◽  
Head Detection ◽  
Linear Transform ◽  
High Level ◽  
Direct Linear Transform

In order to accompany the swimming coaches in evaluating high-level swimmers, we developed a prototype for instantaneous speed estimation. To achieve this, we proposed and validated, in a previous work, a swimmer tracking system based on data fusion. However, the initialization phase is done manually, and our aim, in this paper, is to automate this process. First, we propose a region of interest localization module that allows the detection of the first appearance of the swimmer in the lane as well as the restriction of the region of interest around him. This module is based on the method a contrario which consists of modeling the random noise corresponding to the water and detecting the structured movement relative to the swimmer motion. To do that, we calibrate the pool using DLT (Direct Linear Transform) technique, extract the concerned lane, apply the frame difference approach to detect the moving objects, and then decompose the lane into blocs and classify them into swimmer motion or noise. Second, in order to detect the swimmer’s head, we propose the Scaled Composite JTC which is based on the NL-JTC correlation technique. The input plane of this latter includes a target and a reference image. The first is the region of interest detected by the method a contrario. The second consists of a Scaled Composite Reference. The tests conducted on real video sequences of French swimming championships (Limoges 2015) showed very good results in terms of region of interest localization and swimmer’s head detection which allows a reliable initialization for the tracking system.

scholarly journals A novel method for robust markerless tracking of rodent paws in 3D

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Omid Haji Maghsoudi ◽  
Annie Vahedipour ◽  
Andrew Spence
Keyword(s):  
High Speed ◽  
Motor Impairment ◽  
The Body ◽  
Matching Problem ◽  
Markerless Tracking ◽  
Automated Method ◽  
Precise Quantification ◽  
Linear Transform ◽  
Novel Method ◽  
Direct Linear Transform

Abstract Studying animal locomotion improves our understanding of motor control and aids in the treatment of motor impairment. Mice are a premier model of human disease and are the model system of choice for much of basic neuroscience. Placement of the tips of appendages, here paws, is typically critical for locomotion. Tracking paws from a video is difficult, however, due to frequent occlusions and collisions. We propose a method and provide software to track the paws of rodents. We use a superpixel-based method to segment the paws, direct linear transform to perform 3D reconstruction, a 3D Kalman filter (KF) to solve the matching problem and label paws across frames, and spline fits through time to resolve common collisions. The automated method was compared to manual tracking. The method had an average of 2.54 mistakes requiring manual correction per 1000 frames with a maximum of 5.29 possible errors while these values were estimates of the expected errors. We present an algorithm and its implementation to track the paws of running rodents. This algorithm can be applied to different animals as long as the tips of the legs can be differentiated from the background and other parts of the body using color features. The presented algorithm provides a robust tool for future studies in multiple fields, where precise quantification of locomotor behavior from a high-speed video is required. We further present a graphical user interface (GUI) to track, visualize, and edit the tracking data.

Study on Camera Pose Estimation

2014 ◽  
Vol 631-632 ◽  
pp. 462-469
Author(s):  
Xiao Zhou Zhu ◽  
Xiao Qian Chen ◽  
Xin Song
Keyword(s):  
Computer Vision ◽  
Comparative Analysis ◽  
Iterative Method ◽  
Pose Estimation ◽  
Camera Pose Estimation ◽  
Qualitative And Quantitative ◽  
Camera Pose ◽  
Linear Transform ◽  
Direct Linear Transform ◽  
Different Levels

A common need in photogrammetry, robotics and computer vision is performing camera pose estimation. A comparative analysis is presented here for three classical and representative algorithms, including direct linear transform (DLT), EPNP and Cayley method, each of which computes the translation and rotation matrix using non-iterative method with six or more point correspondences. The comparison shows qualitative and quantitative experimental results to determine (1) the accuracy and robustness under the influence of different levels of noise, (2) the accuracy, robustness and efficiency for different sizes of point correspondences.

3D modeling of running rodents based on direct linear transform

2017 ◽  
Author(s):  
Omid Haji Maghsoudi ◽  
Annie Vahedipour Tabrizi ◽  
Benjamin Robertson ◽  
Andrew Spence
Keyword(s):  
3D Modeling ◽  
Linear Transform ◽  
Direct Linear Transform

X-ray microtomography

1988 ◽  
Vol 46 ◽  
pp. 998-999
Author(s):  
H.W. Deckman ◽  
B.F. Flannery ◽  
J.H. Dunsmuir ◽  
K.D' Amico
Keyword(s):  
Computed Tomography ◽  
Internal Structure ◽  
Imaging Technique ◽  
Three Dimensional ◽  
Tissue Structure ◽  
Individual Element ◽  
X Ray ◽  
Non Invasive ◽  
Panoramic Imaging ◽  
Three Dimensional Images

We have developed a new X-ray microscope which produces complete three dimensional images of samples. The microscope operates by performing X-ray tomography with unprecedented resolution. Tomography is a non-invasive imaging technique that creates maps of the internal structure of samples from measurement of the attenuation of penetrating radiation. As conventionally practiced in medical Computed Tomography (CT), radiologists produce maps of bone and tissue structure in several planar sections that reveal features with 1mm resolution and 1% contrast. Microtomography extends the capability of CT in several ways. First, the resolution which approaches one micron, is one thousand times higher than that of the medical CT. Second, our approach acquires and analyses the data in a panoramic imaging format that directly produces three-dimensional maps in a series of contiguous stacked planes. Typical maps available today consist of three hundred planar sections each containing 512x512 pixels. Finally, and perhaps of most import scientifically, microtomography using a synchrotron X-ray source, allows us to generate maps of individual element.

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