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Object recognition by genetic algorithm
Title
Object recognition by genetic algorithm.
Creator
Li, Jianhua., Florida Atlantic University, Han, Chingping (Jim), Zhuang, Hanqi, College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description
Vision systems have been widely used for parts inspection in electronics assembly lines. In order to improve the overall performance of a visual inspection system, it is important to employ an efficient object recognition algorithm. In this thesis work, a genetic algorithm based correlation algorithm is designed for the task of visual electronic parts inspection. The proposed procedure is composed of two stages. In the first stage, a genetic algorithm is devised to find a sufficient number of...
Show moreVision systems have been widely used for parts inspection in electronics assembly lines. In order to improve the overall performance of a visual inspection system, it is important to employ an efficient object recognition algorithm. In this thesis work, a genetic algorithm based correlation algorithm is designed for the task of visual electronic parts inspection. The proposed procedure is composed of two stages. In the first stage, a genetic algorithm is devised to find a sufficient number of candidate image windows. For each candidate window, the correlation is performed between the sampled template and the image pattern inside the window. In the second stage, local searches are conducted in the neighborhood of these candidate windows. Among all the searched locations, the one that has a highest correlation value with the given template is selected as the best matched location. To apply the genetic algorithm technique, a number of important issues, such as selection of a fitness function, design of a coding scheme, and tuning of genetic parameters are addressed in the thesis. Experimental studies have confirmed that the proposed GA-based correlation method is much more effective in terms of accuracy and speed in locating the desired object, compared with the existing Monte-Carlo random search method.
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Date Issued
1995
PURL
http://purl.flvc.org/fcla/dt/15225
Subject Headings
Genetic algorithms, Robots--Control systems, Computer vision, Quality control--Optical methods
Format
Document (PDF)
Event detection in surveillance video
Title
Event detection in surveillance video.
Creator
Castellanos Jimenez, Ricardo Augusto., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
Digital video is being used widely in a variety of applications such as entertainment, surveillance and security. Large amount of video in surveillance and security requires systems capable to processing video to automatically detect and recognize events to alleviate the load on humans and enable preventive actions when events are detected. The main objective of this work is the analysis of computer vision techniques and algorithms used to perform automatic detection of events in video...
Show moreDigital video is being used widely in a variety of applications such as entertainment, surveillance and security. Large amount of video in surveillance and security requires systems capable to processing video to automatically detect and recognize events to alleviate the load on humans and enable preventive actions when events are detected. The main objective of this work is the analysis of computer vision techniques and algorithms used to perform automatic detection of events in video sequences. This thesis presents a surveillance system based on optical flow and background subtraction concepts to detect events based on a motion analysis, using an event probability zone definition. Advantages, limitations, capabilities and possible solution alternatives are also discussed. The result is a system capable of detecting events of objects moving in opposing direction to a predefined condition or running in the scene, with precision greater than 50% and recall greater than 80%.
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Date Issued
2010
PURL
http://purl.flvc.org/FAU/1870694
Subject Headings
Computer systems, Security measures, Image processing, Digital techniques, Imaging systems, Mathematical models, Pattern recognition systems, Computer vision, Digital video
Format
Document (PDF)
The Effect of Stereoscopic Cues on Multiple Object Tracking in a 3D Virtual Environment
Title
The Effect of Stereoscopic Cues on Multiple Object Tracking in a 3D Virtual Environment.
Creator
Oliveira, Steven Milanez, Barenholtz, Elan, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Psychology
Abstract/Description
Research on Multiple Object Tracking (MOT) has typically involved 2D displays where stimuli move in a single depth plane. However, under natural conditions, objects move in 3D which adds complexity to tracking. According to the spatial interference model, tracked objects have an inhibitory surround that when crossed causes tracking errors. How do these inhibitory fields translate to 3D space? Does multiple object tracking operate on a 2D planar projection, or is it in fact 3D? To investigate...
Show moreResearch on Multiple Object Tracking (MOT) has typically involved 2D displays where stimuli move in a single depth plane. However, under natural conditions, objects move in 3D which adds complexity to tracking. According to the spatial interference model, tracked objects have an inhibitory surround that when crossed causes tracking errors. How do these inhibitory fields translate to 3D space? Does multiple object tracking operate on a 2D planar projection, or is it in fact 3D? To investigate this, we used a fully immersive virtual-reality environment where participants were required to track 1 to 4 moving objects. We compared performance to a condition where participants viewed the same stimuli on a computer screen with monocular depth cues. Results suggest that participants were more accurate in the VR condition than the computer screen condition. This demonstrates interference is negligent when the objects are spatially distant, yet proximate within the 2D projection.
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Date Issued
2017
PURL
http://purl.flvc.org/fau/fd/FA00004943, http://purl.flvc.org/fau/fd/FA00004943
Subject Headings
Pattern perception., Virtual reality., Interactive multimedia., Computer simulation., Computer vision--Mathematical models., Automatic tracking--Mathematical models.
Format
Document (PDF)
Face Processing Using Mobile Devices
Title
Face Processing Using Mobile Devices.
Creator
James, Jhanon, Marques, Oge, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
Image Processing and Computer Vision solutions have become commodities for software developers, thanks to the growing availability of Application Program- ming Interfaces (APIs) that encapsulate rich functionality, powered by advanced al- gorithms. To understand and create an e cient method to process faces in images by computers, one must understand how the human visual system processes them. Face processing by computers has been an active research area for about 50 years now. Face detection...
Show moreImage Processing and Computer Vision solutions have become commodities for software developers, thanks to the growing availability of Application Program- ming Interfaces (APIs) that encapsulate rich functionality, powered by advanced al- gorithms. To understand and create an e cient method to process faces in images by computers, one must understand how the human visual system processes them. Face processing by computers has been an active research area for about 50 years now. Face detection has become a commodity and is now incorporated into simple devices such as digital cameras and smartphones. An iOS app was implemented in Objective-C using Microsoft Cognitive Ser- vices APIs, as a tool for human vision and face processing research. Experimental work on image compression, upside-down orientation, the Thatcher e ect, negative inversion, high frequency, facial artifacts, caricatures and image degradation were completed on the Radboud and 10k US Adult Faces Databases along with other images.
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Date Issued
2016
PURL
http://purl.flvc.org/fau/fd/FA00004770, http://purl.flvc.org/fau/fd/FA00004770
Subject Headings
Image processing--Digital techniques., Mobile communication systems., Mobile computing., Artificial intelligence., Human face recognition (Computer science), Computer vision., Optical pattern recognition.
Format
Document (PDF)
Sparse Modeling Applied to Patient Identification for Safety in Medical Physics Applications
Title
Sparse Modeling Applied to Patient Identification for Safety in Medical Physics Applications.
Creator
Lewkowitz, Stephanie, Kalantzis, Georgios, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Physics
Abstract/Description
Every scheduled treatment at a radiation therapy clinic involves a series of safety protocol to ensure the utmost patient care. Despite safety protocol, on a rare occasion an entirely preventable medical event, an accident, may occur. Delivering a treatment plan to the wrong patient is preventable, yet still is a clinically documented error. This research describes a computational method to identify patients with a novel machine learning technique to combat misadministration.The patient...
Show moreEvery scheduled treatment at a radiation therapy clinic involves a series of safety protocol to ensure the utmost patient care. Despite safety protocol, on a rare occasion an entirely preventable medical event, an accident, may occur. Delivering a treatment plan to the wrong patient is preventable, yet still is a clinically documented error. This research describes a computational method to identify patients with a novel machine learning technique to combat misadministration.The patient identification program stores face and fingerprint data for each patient. New, unlabeled data from those patients are categorized according to the library. The categorization of data by this face-fingerprint detector is accomplished with new machine learning algorithms based on Sparse Modeling that have already begun transforming the foundation of Computer Vision. Previous patient recognition software required special subroutines for faces and di↵erent tailored subroutines for fingerprints. In this research, the same exact model is used for both fingerprints and faces, without any additional subroutines and even without adjusting the two hyperparameters. Sparse modeling is a powerful tool, already shown utility in the areas of super-resolution, denoising, inpainting, demosaicing, and sub-nyquist sampling, i.e. compressed sensing. Sparse Modeling is possible because natural images are inherrently sparse in some bases, due to their inherrant structure. This research chooses datasets of face and fingerprint images to test the patient identification model. The model stores the images of each dataset as a basis (library). One image at a time is removed from the library, and is classified by a sparse code in terms of the remaining library. The Locally Competetive Algorithm, a truly neural inspired Artificial Neural Network, solves the computationally difficult task of finding the sparse code for the test image. The components of the sparse representation vector are summed by `1 pooling, and correct patient identification is consistently achieved 100% over 1000 trials, when either the face data or fingerprint data are implemented as a classification basis. The algorithm gets 100% classification when faces and fingerprints are concatenated into multimodal datasets. This suggests that 100% patient identification will be achievable in the clinal setting.
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Date Issued
2016
PURL
http://purl.flvc.org/fau/fd/FA00004721, http://purl.flvc.org/fau/fd/FA00004721
Subject Headings
Computer vision in medicine, Diagnostic imaging -- Data processing, Mathematical models, Medical errors -- Prevention, Medical physics, Sampling (Statistics)
Format
Document (PDF)
Design of an Aquatic Quadcopter with Optical Wireless Communications
Title
Design of an Aquatic Quadcopter with Optical Wireless Communications.
Creator
Haller, Patterson, Abtahi, Homayoon, Florida Atlantic University, College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description
With a focus on dynamics and control, an aquatic quadcopter with optical wireless communications is modeled, designed, constructed, and tested. Optical transmitter and receiver circuitry is designed and discussed. By utilization of the small angle assumption, the nonlinear dynamics of quadcopter movement are linearized around an equilibrium state of zero motion. The set of equations are then tentatively employed beyond limit of the small angle assumption, as this work represents an initial...
Show moreWith a focus on dynamics and control, an aquatic quadcopter with optical wireless communications is modeled, designed, constructed, and tested. Optical transmitter and receiver circuitry is designed and discussed. By utilization of the small angle assumption, the nonlinear dynamics of quadcopter movement are linearized around an equilibrium state of zero motion. The set of equations are then tentatively employed beyond limit of the small angle assumption, as this work represents an initial explorative study. Specific constraints are enforced on the thrust output of all four rotors to reduce the multiple-input multiple-output quadcopter dynamics to a set of single-input single-output systems. Root locus and step response plots are used to analyze the roll and pitch rotations of the quadcopter. Ultimately a proportional integral derivative based control system is designed to control the pitch and roll. The vehicle’s yaw rate is similarly studied to develop a proportional controller. The prototype is then implemented via an I2C network of Arduino microcontrollers and supporting hardware.
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Date Issued
2016
PURL
http://purl.flvc.org/fau/fd/FA00004786, http://purl.flvc.org/fau/fd/FA00004786
Subject Headings
Autonomous robots--Design and construction., Embedded computer systems--Design and construction., Wireless communication systems., Artificial intelligence., Optical pattern recognition., Computer vision.
Format
Document (PDF)
Stereo vision-based target tracking system for USV operations
Title
Stereo vision-based target tracking system for USV operations.
Creator
Sinisterra, Armando Jose, Dhanak, Manhar R., Florida Atlantic University, College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description
A methodology to estimate the state of a moving marine vehicle, defined by its position, velocity and heading, from an unmanned surface vehicle (USV), also in motion, using a stereo vision-based system, is presented in this work, in support of following a target vehicle using an USV.
Date Issued
2015
PURL
http://purl.flvc.org/fau/fd/FA00004466, http://purl.flvc.org/fau/fd/FA00004466
Subject Headings
Adaptive control systems, Adaptive signal processing, Computer vision, Inertial navigation systems, Intelligent control systems, Motion segmentaton, Oceanographic instruments -- Development, Ubiquitous computing
Format
Document (PDF)
An Intelligent Method For Violence Detection in Live Video Feeds
Title
An Intelligent Method For Violence Detection in Live Video Feeds.
Creator
Eneim, Maryam, Marques, Oge, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
In the past few years, violence detection has become an increasingly rele- vant topic in computer vision with many proposed solutions by researchers. This thesis proposes a solution called Criminal Aggression Recognition Engine (CARE), an OpenCV based Java implementation of a violence detection system that can be trained with video datasets to classify action in a live feed as non-violent or violent. The algorithm extends existing work on fast ght detection by implementing violence detection...
Show moreIn the past few years, violence detection has become an increasingly rele- vant topic in computer vision with many proposed solutions by researchers. This thesis proposes a solution called Criminal Aggression Recognition Engine (CARE), an OpenCV based Java implementation of a violence detection system that can be trained with video datasets to classify action in a live feed as non-violent or violent. The algorithm extends existing work on fast ght detection by implementing violence detection of live video, in addition to prerecorded video. The results for violence detection in prerecorded videos are comparable to other popular detection systems and the results for live video are also very encouraging, making the work proposed in this thesis a solid foundation for improved live violence detection systems.
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Date Issued
2016
PURL
http://purl.flvc.org/fau/fd/FA00004775, http://purl.flvc.org/fau/fd/FA00004775
Subject Headings
Multimedia systems., Image analysis., Computer vision., Visual communication--Social aspects., Social problems--21st century., Pattern recognition systems., Optical pattern recognition.
Format
Document (PDF)

Pages