Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 25 of 25

Full-Text Articles in Engineering

Efficient Scopeformer: Towards Scalable And Rich Feature Extraction For Intracranial Hemorrhage Detection Using Hybrid Convolution And Vision Transformer Networks, Yassine Barhoumi Mar 2023

Efficient Scopeformer: Towards Scalable And Rich Feature Extraction For Intracranial Hemorrhage Detection Using Hybrid Convolution And Vision Transformer Networks, Yassine Barhoumi

Theses and Dissertations

The field of medical imaging has seen significant advancements through the use of artificial intelligence (AI) techniques. The success of deep learning models in this area has led to the need for further research. This study aims to explore the use of various deep learning algorithms and emerging modeling techniques to improve training paradigms in medical imaging. Convolutional neural networks (CNNs) are the go-to architecture for computer vision problems, but they have limitations in mapping long-term dependencies within images. To address these limitations, the study explores the use of techniques such as global average pooling and self-attention mechanisms. Additionally, the …


Learning To Detect Pedestrian Flow In Traffic Intersections From Synthetic Data, Abhijit Baul May 2021

Learning To Detect Pedestrian Flow In Traffic Intersections From Synthetic Data, Abhijit Baul

Theses and Dissertations

Detecting pedestrian flow in different directions at at traffic-intersection has always been a challenging task. Challenges include different weather conditions, different crowd densities, occlusions, lack of available data, and so on. The emergence of deep learning and computer vision algorithms has shown promises to deal with these problems. Most of the recent works only focus on either detecting combined pedestrian flow or counting the total number of pedestrians. In this work, we have tried to detect not only combined pedestrian flow but also pedestrian flow indifferent directions. Our contributions are, 1) we are introducing a synthetic pedestrian dataset that we …


Using Motion Capture And Augmented Reality To Test Aar With Boom Occlusion, Vincent J. Bownes Mar 2021

Using Motion Capture And Augmented Reality To Test Aar With Boom Occlusion, Vincent J. Bownes

Theses and Dissertations

The operational capability of drones is limited by their inability to perform aerial refueling. This can be overcome by automating the process with a computer vision solution. Previous work has demonstrated the feasibility of automated aerial refueling (AAR) in simulation. To progress this technique to the real world, this thesis conducts experiments using real images of a physical aircraft replica and a motion capture system for truth data. It also compares the error between the real and virtual experiments to validate the fidelity of the simulation. Results indicate that the current technique is effective on real images and that the …


Object Detection With Deep Learning To Accelerate Pose Estimation For Automated Aerial Refueling, Andrew T. Lee Mar 2020

Object Detection With Deep Learning To Accelerate Pose Estimation For Automated Aerial Refueling, Andrew T. Lee

Theses and Dissertations

Remotely piloted aircraft (RPAs) cannot currently refuel during flight because the latency between the pilot and the aircraft is too great to safely perform aerial refueling maneuvers. However, an AAR system removes this limitation by allowing the tanker to directly control the RP A. The tanker quickly finding the relative position and orientation (pose) of the approaching aircraft is the first step to create an AAR system. Previous work at AFIT demonstrates that stereo camera systems provide robust pose estimation capability. This thesis first extends that work by examining the effects of the cameras' resolution on the quality of pose …


Maximizing Accuracy Through Stereo Vision Camera Positioning For Automated Aerial Refueling, Kirill A. Sarantsev Mar 2020

Maximizing Accuracy Through Stereo Vision Camera Positioning For Automated Aerial Refueling, Kirill A. Sarantsev

Theses and Dissertations

Aerial refueling is a key component of the U.S. Air Force strategic arsenal. When two aircraft interact in an aerial refueling operation, the accuracy of relative navigation estimates are critical for the safety, accuracy and success of the mission. Automated Aerial Refueling (AAR) looks to improve the refueling process by creating a more effective system and allowing for Unmanned Aerial Vehicle(s) (UAV) support. This paper considers a cooperative aerial refueling scenario where stereo cameras are used on the tanker to direct a \boom" (a large, long structure through which the fuel will ow) into a port on the receiver aircraft. …


Use Of Lidar In Automated Aerial Refueling To Improve Stereo Vision Systems, Michael R. Crowl Mar 2020

Use Of Lidar In Automated Aerial Refueling To Improve Stereo Vision Systems, Michael R. Crowl

Theses and Dissertations

The United States Air Force (USAF) executes five Core Missions, four of which depend on increased aircraft range. To better achieve global strike and reconnaissance, unmanned aerial vehicles (UAVs) require aerial refueling for extended missions. However, current aerial refueling capabilities are limited to manned aircraft due to technical difficulties to refuel UAVs mid-flight. The latency between a UAV operator and the UAV is too large to adequately respond for such an operation. To overcome this limitation, the USAF wants to create a capability to guide the refueling boom into the refueling receptacle. This research explores the use of light detection …


Emotion Recognition Using Facial Feature Extraction, Demiyan Smirnov Jul 2019

Emotion Recognition Using Facial Feature Extraction, Demiyan Smirnov

Theses and Dissertations

Computerized emotion recognition systems can be powerful tools to help solve problems in a wide range of fields including education, healthcare, and marketing. Existing systems use digital images or live video to track facial expressions on a person's face and deduce that person's emotional state. The research presented in this thesis explores combinations of several facial feature extraction techniques with different classifier algorithms. Namely, the feature extraction techniques used in this research were Discrete Cosine/Sine Transforms, Fast Walsh-Hadamard Transform, Principle Component Analysis, and a novel method called XPoint. Features were extracted from both global (using the entire facial image) and …


An Efficient Feature Descriptor And Its Real-Time Applications, Alok Desai Jun 2015

An Efficient Feature Descriptor And Its Real-Time Applications, Alok Desai

Theses and Dissertations

Finding salient features in an image, and matching them to their corresponding features in another image is an important step for many vision-based applications. Feature description plays an important role in the feature matching process. A robust feature descriptor must works with a number of image deformations and should be computationally efficient. For resource-limited systems, floating point and complex operations such as multiplication and square root are not desirable. This research first introduces a robust and efficient feature descriptor called PRObability (PRO) descriptor that meets these requirements without sacrificing matching accuracy. The PRO descriptor is further improved by incorporating only …


Real-Time Color Treebasis Feature Matching On A Limited-Resource Hardware System, Garrett Sean Hartman Oct 2013

Real-Time Color Treebasis Feature Matching On A Limited-Resource Hardware System, Garrett Sean Hartman

Theses and Dissertations

This research has been conducted in order to create a robust, lightweight feature detecting and matching algorithm that builds upon the foundation set by the TreeBASIS algorithm. The goal is to create a color-based version of the TreeBASIS algorithm that uses less hardware resources than the original, is more accurate in its matching capabilities, can successfully be deployed on a resource-limited FPGA platform, and can process in real time. This thesis first presents the newly designed hardware tri-channel FAST Feature Detector that finds features in color. Next the TreeBASIS algorithm is analyzed to discover what improvements can be made in …


Limited Resource Feature Detection, Description, And Matching, Spencer G. Fowers Apr 2012

Limited Resource Feature Detection, Description, And Matching, Spencer G. Fowers

Theses and Dissertations

The aims of this research work are to develop a feature detection, description, and matching system for low-resource applications. This work was motivated by the need for a vision sensor to assist the flight of a quad-rotor UAV. This application presented a real-world challenge of autonomous drift stabilization using vision sensors. The initial solution implemented a basic feature detector and matching system on an FPGA. The research then pursued ways to improve the vision system. Research began with color feature detection, and the Color Difference of Gaussians feature detector was developed. CDoG provides better results than gray scale DoG and …


Covariance Analysis Of Vision Aided Navigation By Bootstrapping, Andrew L. Relyea Mar 2012

Covariance Analysis Of Vision Aided Navigation By Bootstrapping, Andrew L. Relyea

Theses and Dissertations

Inertial Navigation System (INS) aiding using bearing measurements taken over time of stationary ground features is investigated. A cross country flight, in two and three dimensional space, is considered, as well as a vertical drop in three dimensional space. The objective is to quantify the temporal development of the uncertainty in the navigation states of an aircraft INS which is aided by taking bearing measurements of ground objects which have been geolocated using ownship position. It is shown that during wings level flight at constant speed and a fixed altitude, an aircraft that tracks ground objects and over time sequentially …


Design Of A Monocular Multi-Spectral Skin Detection, Melanin Estimation, And False-Alarm Suppression System, Keith R. Peskosky Mar 2010

Design Of A Monocular Multi-Spectral Skin Detection, Melanin Estimation, And False-Alarm Suppression System, Keith R. Peskosky

Theses and Dissertations

A real-time skin detection, false-alarm reduction, and melanin estimation system is designed targeting search and rescue (SAR) with application to special operations for manhunting and human measurement and signatures intelligence. A mathematical model of the system is developed and used to determine how the physical system performs under illumination, target-to-sensor distance, and target-type scenarios. This aspect is important to the SAR community to gain an understanding of the deployability in different operating environments. A multi-spectral approach is developed and consists of two short-wave infrared cameras and two visible cameras. Through an optical chain of lenses, custom designed and fabricated dichroic …


Electronic Image Stabilization For Mobile Robotic Vision Systems, Michael John Smith Sep 2009

Electronic Image Stabilization For Mobile Robotic Vision Systems, Michael John Smith

Theses and Dissertations

When a camera is affixed on a dynamic mobile robot, image stabilization is the first step towards more complex analysis on the video feed. This thesis presents a novel electronic image stabilization (EIS) algorithm for small inexpensive highly dynamic mobile robotic platforms with onboard camera systems. The algorithm combines optical flow motion parameter estimation with angular rate data provided by a strapdown inertial measurement unit (IMU). A discrete Kalman filter in feedforward configuration is used for optimal fusion of the two data sources. Performance evaluations are conducted by a simulated video truth model (capturing the effects of image translation, rotation, …


Real-Time Optical Flow Sensor Design And Its Application On Obstacle Detection, Zhaoyi Wei Apr 2009

Real-Time Optical Flow Sensor Design And Its Application On Obstacle Detection, Zhaoyi Wei

Theses and Dissertations

Motion is one of the most important features describing an image sequence. Motion estimation has been widely applied in structure from motion, vision-based navigation and many other fields. However, real-time motion estimation remains a challenge because of its high computational expense. The traditional CPU-based scheme cannot satisfy the power, size and computation requirements in many applications. With the availability of new parallel architectures such as FPGAs and GPUs, applying these new technologies to computer vision tasks such as motion estimation has been an active research field in recent years. In this dissertation, FPGAs have been applied to real-time motion estimation …


An Optical Flow Implementation Comparison Study, John M. Bodily Mar 2009

An Optical Flow Implementation Comparison Study, John M. Bodily

Theses and Dissertations

Optical flow is the apparent motion of brightness patterns within an image scene. Algorithms used to calculate the optical flow for a sequence of images are useful in a variety of applications, including motion detection and obstacle avoidance. Typical optical flow algorithms are computationally intense and run slowly when implemented in software, which is problematic since many potential applications of the algorithm require real-time calculation in order to be useful. To increase performance of the calculation, optical flow has recently been implemented on FPGA and GPU platforms. These devices are able to process optical flow in real-time, but are generally …


Model-Based Control Using Model And Mechanization Fusion Techniques For Image-Aided Navigation, Constance D. Hendrix Mar 2009

Model-Based Control Using Model And Mechanization Fusion Techniques For Image-Aided Navigation, Constance D. Hendrix

Theses and Dissertations

Unmanned aerial vehicles are no longer used for just reconnaissance. Current requirements call for smaller autonomous vehicles that replace the human in high-risk activities. Many times these activities are performed in GPS-degraded environments. Without GPS providing today's most accurate navigation solution, autonomous navigation in tight areas is more difficult. Today, image-aided navigation is used and other methods are explored to more accurately navigate in such areas (e.g., indoors). This thesis explores the use of inertial measurements and navigation solution updates using cameras with a model-based Linear Quadratic Gaussian controller. To demonstrate the methods behind this research, the controller will provide …


Communication Free Robot Swarming, Zachary C. Gray Feb 2009

Communication Free Robot Swarming, Zachary C. Gray

Theses and Dissertations

As the military use of unmanned aerial vehicles increases, a growing need for novel strategies to control these systems exists. One such method for controlling many unmanned aerial vehicles simultaneously is the through the use of swarm algorithms. This research explores a swarm robotic algorithm developed by Kadrovach implemented on Pioneer Robots in a real-world environment. An adaptation of his visual sensor is implemented using stereo vision as the primary method of sensing the environment. The swarm members are prohibited from explicitly communicating other than passively through the environment. The resulting implementation produces a communication free swarming algorithm. The algorithm …


Real-Time Forward Urban Environment Perception For An Autonomous Ground Vehicle Using Computer Vision And Lidar, Christopher Richard Greco Mar 2008

Real-Time Forward Urban Environment Perception For An Autonomous Ground Vehicle Using Computer Vision And Lidar, Christopher Richard Greco

Theses and Dissertations

The field of autonomous vehicle research is growing rapidly. The Congressional mandate for the military to use unmanned vehicles has, in large part, sparked this growth. In conjunction with this mandate, DARPA sponsored the Urban Challenge, a competition to create fully autonomous vehicles that can operate in urban settings. An extremely important feature of autonomous vehicles, especially in urban locations, is their ability to perceive their environment. The research presented in this thesis is directed toward providing an autonomous vehicle with real-time data that efficiently and compactly represents its forward environment as it navigates an urban area. The information extracted …


Particle Filter Based Mosaicking For Forest Fire Tracking, Justin Mathew Bradley Jul 2007

Particle Filter Based Mosaicking For Forest Fire Tracking, Justin Mathew Bradley

Theses and Dissertations

Using autonomous miniature air vehicles (MAVs) is a cost-effective, simple method for collecting data about the size, shape, and location characteristics of a forest fire. However, noise in measurements used to compute pose (location and attitude) of the on-board camera leads to significant errors in the processing of collected video data. Typical methods using MAVs to track fires attempt to find single geolocation estimates and filter that estimate with subsequent observations. While this is an effective method of resolving the noise to achieve a better geolocation estimate, it reduces a fire to a single point or small set of points. …


Obstacle Avoidance For Small Unmanned Air Vehicles, Brandon R. Call Sep 2006

Obstacle Avoidance For Small Unmanned Air Vehicles, Brandon R. Call

Theses and Dissertations

Small UAVs are used for low altitude surveillance flights where unknown obstacles can be encountered. These UAVs can be given the capability to navigate in uncertain environments if obstacles are identified. This research presents an obstacle avoidance system for small UAVs. First, a mission waypoint path is created that avoids all known obstacles using a genetic algorithm. Then, while the UAV is in flight, obstacles are detected using a forward looking, onboard camera. Image features are found using the Harris Corner Detector and tracked through multiple video frames which provides three dimensional localization of the features. A sparse three dimensional …


Structure From Motion Using Optical Flow Probability Distributions, Paul Clark Merrell Mar 2005

Structure From Motion Using Optical Flow Probability Distributions, Paul Clark Merrell

Theses and Dissertations

Several novel structure from motion algorithms are presented that are designed to more effectively manage the problem of noise. In many practical applications, structure from motion algorithms fail to work properly because of the noise in the optical flow values. Most structure from motion algorithms implicitly assume that the noise is identically distributed and that the noise is white. Both assumptions are false. Some points can be track more easily than others and some points can be tracked more easily in a particular direction. The accuracy of each optical flow value can be quantified using an optical flow probability distribution. …


Determination Of Structure From Motion Using Aerial Imagery, Paul R. Graham Mar 2005

Determination Of Structure From Motion Using Aerial Imagery, Paul R. Graham

Theses and Dissertations

The structure from motion process creates three-dimensional models from a sequence of images. Until recently, most research in this field has been restricted to land-based imagery. This research examines the current methods of land-based structure from motion and evaluates their performance for aerial imagery. Current structure from motion algorithms search the initial image for features to track though the subsequent images. These features are used to create point correspondences between the two images. The correspondences are used to estimate the motion of the camera and then the three-dimensional structure of the scene. This research tests current algorithms using synthetic data …


Discovering The Merit Of The Wavelet Transform For Object Classification, Matthew D. Eyster Mar 2004

Discovering The Merit Of The Wavelet Transform For Object Classification, Matthew D. Eyster

Theses and Dissertations

Vision is the primary sense by which most biological systems collect information about their environment. Computer vision is a branch of artificial intelligence concerned with endowing machines with the ability to understand images. Object recognition is a key part of machine vision with far reaching benefits ranging from target recognition, surveillance systems, to automation systems. Extraction of salient features from an image is one of the key steps in object recognition. Typically, geometric primitives are extracted from an image using local analysis. However, the wavelet transform provides a global approach with good locality. Additionally, the directional and multiresolution properties may …


Realtime Color Stereovision Processing, Byron P. Formwalt Mar 2000

Realtime Color Stereovision Processing, Byron P. Formwalt

Theses and Dissertations

Recent developments in aviation have made micro air vehicles (MAVs) a reality. These featherweight palm-sized radio-controlled flying saucers embody the future of air-to-ground combat. No one has ever successfully implemented an autonomous control system for MAVs. Because MAVs are physically small with limited energy supplies, video signals offer superiority over radar for navigational applications. This research takes a step forward in real time machine vision processing. It investigates techniques for implementing a real time stereovision processing system using two miniature color cameras. The effects of poor-quality optics are overcome by a robust algorithm, which operates in real time and achieves …


Image Analysis Using Gabor Transforms: Correlated With Human Saccadic Movement Data To Identify The Human Visual Search Strategy, Ralph J. St John Dec 1991

Image Analysis Using Gabor Transforms: Correlated With Human Saccadic Movement Data To Identify The Human Visual Search Strategy, Ralph J. St John

Theses and Dissertations

This thesis investigated whether a relationship exists between the Gabor Correlation Coefficient (GCC) magnitudes of fixation points for a set of images viewed by six subjects and the human visual search strategy. A couple of different relationships were investigated. First, the data were analyzed to determine if the GCC magnitudes of human fixation points predicted the time ordered sequence of human fixation points during the performance of a visual search. Second, the data were analyzed to determine if there was a significant difference between the GCC magnitudes of the human fixation points and the GCC magnitudes of a random set …