Signal Processing Commons^™

Leveraging Machine-Learning Algorithms In Two Car Crash Detection Systems On A Custom Dataset, Addison Jacob Sandvik

Master's Theses

Traffic accidents pose a significant threat to public safety, causing millions of deaths and injuries worldwide each year. While efforts to reduce accidents have seen limited progress in recent years, improving emergency response times through automated detection systems is a promising avenue for saving lives. This thesis describes the development of machine learning-based traffic accident detection systems, exploring both video classification and image detection models. The models are trained on a new dataset deemed the Cal Poly Traffic Accident Dataset, an extension of the existing Car Accident Detection and Prediction (CADP) dataset with a precise collision annotations. Two systems were …

A Heuristic Approach To Portrait Segmentation And Its Application To Synthetic Bokeh Generation, Charles J. Snead

Master's Theses

Segmentation of portrait images is an important technique used to separate the foreground and background of an image. This separation of layers is useful for selectively applying post-processing techniques to enhance the quality of the image, such as blurring the background. Automatic portrait segmentation is a complex process that can be completed with a high degree of accuracy using deep learning with neural networks, but training and inference are often very computationally expensive. This thesis aims to take a heuristic approach to portrait segmentation by combining classical image processing and computer vision techniques into a solution that can be run …

Iris Detection Authenticator, Nathan D. Tang, Bryan K. Chau

Electrical Engineering

The development of iris biometric identification recognition is presented. Iris recognition differs from other methods because data acquisition is non-physical and is more accessible. It has been proven that the iris does not change as an individual ages and is well protected from external damages due to the eyelid and cornea, acting as a shield to the iris. In addition, the iris is almost impossible to forge due to its complex patterns and the current limitations in technology. Using Canny Edge Detection, Hough Transform, rubber-sheet normalization, Histogram of Gradient feature extraction, and the MultiMedia University iris database as our subjects, …

Deep Models For Improving The Performance And Reliability Of Person Recognition, Sobhan Soleymani

Graduate Theses, Dissertations, and Problem Reports (ETD)

Deep models have provided high accuracy for different applications such as person recognition, image segmentation, image captioning, scene description, and action recognition. In this dissertation, we study the deep learning models and their application in improving the performance and reliability of person recognition. This dissertation focuses on five aspects of person recognition: (1) multimodal person recognition, (2) quality-aware multi-sample person recognition, (3) text-independent speaker verification, (4) adversarial iris examples, and (5) morphed face images. First, we discuss the application of multimodal networks consisting of face, iris, fingerprint, and speech modalities in person recognition. We propose multi-stream convolutional neural network architectures …

Visual Speech Recognition Using A 3d Convolutional Neural Network, Matthew Rochford

Master's Theses

Main stream automatic speech recognition (ASR) makes use of audio data to identify spoken words, however visual speech recognition (VSR) has recently been of increased interest to researchers. VSR is used when audio data is corrupted or missing entirely and also to further enhance the accuracy of audio-based ASR systems. In this research, we present both a framework for building 3D feature cubes of lip data from videos and a 3D convolutional neural network (CNN) architecture for performing classification on a dataset of 100 spoken words, recorded in an uncontrolled envi- ronment. Our 3D-CNN architecture achieves a testing accuracy of …

Estimation And Prediction Of The Human Gait Dynamics For The Control Of An Ankle-Foot Prosthesis, Guilherme Aramizo Ribeiro

Dissertations, Master's Theses and Master's Reports

With the growing population of amputees, powered prostheses can be a solution to improve the quality of life for many people. Powered ankle-foot prostheses can be made to behave similar to the lost limb via controllers that emulate the mechanical impedance of the human ankle. Therefore, the understanding of human ankle dynamics is of major significance. First, this work reports the modulation of the mechanical impedance via two mechanisms: the co-contraction of the calf muscles and a change of mean ankle torque and angle. Then, the mechanical impedance of the ankle was determined, for the first time, as a multivariable …

Corridor Navigation For Monocular Vision Mobile Robots, Matthew James Ng

Master's Theses

Monocular vision robots use a single camera to process information about its environment. By analyzing this scene, the robot can determine the best navigation direction. Many modern approaches to robot hallway navigation involve using a plethora of sensors to detect certain features in the environment. This can be laser range finders, inertial measurement units, motor encoders, and cameras.

By combining all these sensors, there is unused data which could be useful for navigation. To draw back and develop a baseline approach, this thesis explores the reliability and capability of solely using a camera for navigation. The basic navigation structure begins …

Mitigating The Effects Of Boom Occlusion On Automated Aerial Refueling Through Shadow Volumes, Zachary C. Paulson

Theses and Dissertations

In flight refueling of Unmanned Aerial Vehicles (UAVs) is critical to the United States Air Force (USAF). However, the large communication latency between a ground-based operator and his/her remote UAV makes docking with a refueling tanker unsafe. This latency may be mitigated by leveraging a tanker-centric stereo vision system. The vision system observes and computes an approaching receiver's relative position and orientation offering a low-latency, high frequency docking solution. Unfortunately, the boom -- an articulated refueling arm responsible for physically pumping fuel into the receiver -- occludes large portions of the receiver especially as the receiver approaches and docks with …

Collaborative Appearance-Based Place Recognition And Improving Place Recognition Using Detection Of Dynamic Objects, Juan Pablo Munoz

Dissertations, Theses, and Capstone Projects

This dissertation makes contributions to the problem of Long-Term Appearance-Based Place Recognition. We present a framework for place recognition in a collaborative scheme and a method to reduce the impact of dynamic objects on place representations. We demonstrate our findings using a state-of-the-art place recognition approach.

We begin in Part I by describing the general problem of place recognition and its importance in applications where accurate localization is crucial. We discuss feature detection and description and also explain the functioning of several place recognition frameworks.

In Part II, we present a novel framework for collaboration between agents from a pure …

Multispectral Identification Array, Zachary D. Eagan

Computer Engineering

The Multispectral Identification Array is a device for taking full image spectroscopy data via the illumination of a subject with sixty-four unique spectra. The array combines images under the illumination spectra to produce an approximate reflectance graph for every pixel in a scene. Acquisition of an entire spectrum allows the array to differentiate objects based on surface material. Spectral graphs produced are highly approximate and should not be used to determine material properties, however the output is sufficiently consistent to allow differentiation and identification of previously sampled subjects. While not sufficiently advanced for use as a replacement to spectroscopy the …

Hybrid Single And Dual Pattern Structured Light Illumination, Minghao Wang

Theses and Dissertations--Electrical and Computer Engineering

Structured Light Illumination is a widely used 3D shape measurement technique in non-contact surface scanning. Multi-pattern based Structured Light Illumination methods reconstruct 3-D surface with high accuracy, but are sensitive to object motion during the pattern projection and the speed of scanning process is relatively long. To reduce this sensitivity, single pattern techniques are developed to achieve a high speed scanning process, such as Composite Pattern (CP) and Modified Composite Pattern (MCP) technique. However, most of single patter techniques have a significant banding artifact and sacrifice the accuracy. We focus on developing SLI techniques can achieve both high speed, high …

Model-Free Method Of Reinforcement Learning For Visual Tasks, Jeff S. Soldate, Jonghoon Jin, Eugenio Culurciello

The Summer Undergraduate Research Fellowship (SURF) Symposium

There has been success in recent years for neural networks in applications requiring high level intelligence such as categorization and assessment. In this work, we present a neural network model to learn control policies using reinforcement learning. It takes a raw pixel representation of the current state and outputs an approximation of a Q value function made with a neural network that represents the expected reward for each possible state-action pair. The action is chosen an \epsilon-greedy policy, choosing the highest expected reward with a small chance of random action. We used gradient descent to update the weights and biases …

Early Forest Fire Heat Plume Detection Using Neural Network Classification Of Spectral Differences Between Long-Wave And Mid-Wave Infrared Regions, Raul-Alexander Aldama

Master's Theses

It is difficult to capture the early signs of a forest fire at night using current visible-spectrum sensor technology. Infrared (IR) light sensors, on the other hand, can detect heat plumes expelled at the initial stages of a forest fire around the clock. Long-wave IR (LWIR) is commonly referred to as the “thermal infrared” region where thermal emissions are captured without the need of, or reflections from, external radiation sources. Mid‑wave IR (MWIR) bands lie between the “thermal infrared” and “reflected infrared” (i.e. short-wave IR) regions. Both LWIR and MWIR spectral regions are able to detect thermal radiation; however, they …