Computer Sciences Commons^™

Detecting Curved Objects Against Cluttered Backgrounds, Jan Prokaj

Electronic Theses and Dissertations

Detecting curved objects against cluttered backgrounds is a hard problem in computer vision. We present new low-level and mid-level features to function in these environments. The low-level features are fast to compute, because they employ an integral image approach, which makes them especially useful in real-time applications. The mid-level features are built from low-level features, and are optimized for curved object detection. The usefulness of these features is tested by designing an object detection algorithm using these features. Object detection is accomplished by transforming the mid-level features into weak classifiers, which then produce a strong classifier using AdaBoost. The resulting …

Multi-View Approaches To Tracking, 3d Reconstruction And Object Class Detection, Saad Khan

Electronic Theses and Dissertations

Multi-camera systems are becoming ubiquitous and have found application in a variety of domains including surveillance, immersive visualization, sports entertainment and movie special effects amongst others. From a computer vision perspective, the challenging task is how to most efficiently fuse information from multiple views in the absence of detailed calibration information and a minimum of human intervention. This thesis presents a new approach to fuse foreground likelihood information from multiple views onto a reference view without explicit processing in 3D space, thereby circumventing the need for complete calibration. Our approach uses a homographic occupancy constraint (HOC), which states that if …

Vegetation Identification Based On Satellite Imagery, Vamsi K.R. Mantena, Ramu Pedada, Srinivas Jakkula, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)

Electrical & Computer Engineering Faculty Publications

Automatic vegetation identification plays an important role in many applications including remote sensing and high performance flight simulations. This paper presents a method to automatically identify vegetation based upon satellite imagery. First, we utilize the ISODATA algorithm to cluster pixels in the images where the number of clusters is determined by the algorithm. We then apply morphological operations to the clustered images to smooth the boundaries between clusters and to fill holes inside clusters. After that, we compute six features for each cluster. These six features then go through a feature selection algorithm and three of them are determined to …

Object Detection And Classification With Applications To Skin Cancer Screening, Jonathan Blackledge, Dmitryi Dubovitskiy

Articles

This paper discusses a new approach to the processes of object detection, recognition and classification in a digital image. The classification method is based on the application of a set of features which include fractal parameters such as the Lacunarity and Fractal Dimension. Thus, the approach used, incorporates the characterisation of an object in terms of its texture.

The principal issues associated with object recognition are presented which includes two novel fast segmentation algorithms for which C++ code is provided. The self-learning procedure for designing a decision making engine using fuzzy logic and membership function theory is also presented and …

Live Surface, Christopher J. Armstrong

Theses and Dissertations

Live Surface allows users to segment and render complex surfaces from 3D image volumes at interactive (sub-second) rates using a novel, Cascading Graph Cut (CGC). Live Surface consists of two phases. (1) Preprocessing for generation of a complete 3D watershed hierarchy followed by tracking of all catchment basin surfaces. (2) User interaction in which, with each mouse movement, the 3D object is selected and rendered in real time. Real-time segmentation is ccomplished by cascading through the 3D watershed hierarchy from the top, applying graph cut successively at each level only to catchment basins bordering the segmented surface from the previous …

Using Computer Vision To Create A 3d Representation Of A Snooker Table For Televised Competition Broadcasting, Hao Guo, Brian Mac Namee

Conference papers

The Snooker Extraction and 3D Builder (SE3DB) is designed to be used as a viewer aid in televised snooker broadcasting. Using a single camera positioned over a snooker table, the system creates a virtual 3D model of the table which can be used to allow audiences view the table from any angle. This would be particularly useful in allowing viewers to determine if particular shots are possible or not. This paper will describe the design, development and evaluation of this system. Particular focus in the paper will be given to the techniques used to recognise and locate the balls on …

Towards A Self-Calibrating Video Camera Network For Content Analysis And Forensics, Imran Junejo

Electronic Theses and Dissertations

Due to growing security concerns, video surveillance and monitoring has received an immense attention from both federal agencies and private firms. The main concern is that a single camera, even if allowed to rotate or translate, is not sufficient to cover a large area for video surveillance. A more general solution with wide range of applications is to allow the deployed cameras to have a non-overlapping field of view (FoV) and to, if possible, allow these cameras to move freely in 3D space. This thesis addresses the issue of how cameras in such a network can be calibrated and how …

Human Identification Using Gait, Murat Eki̇nci̇

Turkish Journal of Electrical Engineering and Computer Sciences

Gait refers to the style of walking of an individual. This paper presents a view-invariant approach for human identification at a distance, using gait recognition. Recognition of a person from their gait is a biometric of increasing interest. Based on principal component analysis (PCA), this paper describes a simple, but efficient approach to gait recognition. Binarized silhouettes of a motion object are represented by 1-D signals, which are the basic image features called distance vectors. The distance vectors are differences between the bounding box and silhouette, and are extracted using 4 projections of the silhouette. Based on normalized correlation of …

Constraint-Based Interpolation, Daniel David Goggins

Theses and Dissertations

Image reconstruction is the process of converting a sampled image into a continuous one prior to transformation and resampling. This reconstruction can be more accurate if two things are known: the process by which the sampled image was obtained and the general characteristics of the original image. We present a new reconstruction algorithm known as Constraint-Based Interpolation, which estimates the sampling functions found in cameras and analyzes properties of real world images in order to produce quality real-world image magnifications. To accomplish this, Constraint-Based Interpolation uses a sensor model that pushes the pixels in an interpolation to more closely match …

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 …

Depth From Defocused Motion, Zarina Myles

Electronic Theses and Dissertations

Motion in depth and/or zooming causes defocus blur. This work presents a solution to the problem of using defocus blur and optical flow information to compute depth at points that defocus when they move. We first formulate a novel algorithm which recovers defocus blur and affine parameters simultaneously. Next we formulate a novel relationship (the blur-depth relationship) between defocus blur, relative object depth and three parameters based on camera motion and intrinsic camera parameters. We can handle the situation where a single image has points which have defocused, got sharper or are focally unperturbed. Moreover, our formulation is valid regardless …

Experience-Based Language Acquisition: A Computational Model Of Human Language Acquisition, Brian Edward Pangburn

LSU Doctoral Dissertations

Almost from the very beginning of the digital age, people have sought better ways to communicate with computers. This research investigates how computers might be enabled to understand natural language in a more humanlike way. Based, in part, on cognitive development in infants, we introduce an open computational framework for visual perception and grounded language acquisition called Experience-Based Language Acquisition (EBLA). EBLA can “watch” a series of short videos and acquire a simple language of nouns and verbs corresponding to the objects and object-object relations in those videos. Upon acquiring this protolanguage, EBLA can perform basic scene analysis to generate …

Autoconfiguration, Registration And Mobility Management For Pervasive Computing, Archan Misra, Subir Das, Anthony Mcauley, Sajal K. Das

Research Collection School Of Computing and Information Systems

In the vision of pervasive computing, users will exchange information and control their environments from anywhere using various wireline/wireless networks and computing devices. We believe that current protocols, such as DHCP, PPP, and Mobile IP, must be enhanced to support pervasive network access. In particular, this article identifies three fundamental functions: autoconfiguration, registration, and mobility management, that need such enhancements. Realizing that the IP autoconfiguration capabilities must be extended to configure routers and large dynamic networks, we first describe our autoconfiguration solution based on the dynamic configuration and distribution protocol (DCDP). Second, we discuss why providing user-specific services over a …

Sicnn Optimisation, Two Dimensional Implementation And Comparison, Grant Walker

Theses : Honours

The study investigates the process of optimisation, implementation and comparison of a Shunting Inhibitory Cellular Neural Network (SICNN) for Edge Detection. Shunting inhibition is lateral inhibition where the inhibition function is nonlinear. Cellular Neural Networks are locally interconnected nonlinear, parallel networks which can exist as either discrete time or continuous networks. The name given to Cellular Neural Networks that use shunting inhibition as their nonlinear cell interactions are called Shunting Inhibitory Cellular Neural Networks. This project report examines some existing edge detectors and thresholding techniques. Then it describes the optimisation of the connection weight matrix for SICNN with Complementary Output …

Knowledge-Based Navigation For Autonomous Road Vehicles, Murat Eki̇nci̇, Franches W.J.Gibbs, Barry T. Thomas

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a computer vision system for an autonomous road vehicle (ARV) that is capable of negotiating complex road networks including road junctions in real time. The ultimate aim of the system is to enable the vehicle to drive automatically along a given complex road network whose geometric description is known. This computer vision system includes three main techniques which are necessary for an ARV: a) road following, b) road junction detection, c) manoeuvring at the road junction. The road following algorithm presents a method of executing a number of algorithms using different methods concurrently, fusing their outputs together …

Adaptive Shape From Shading, Ati̇lla Gülteki̇n, Muhi̇tti̇n Gökmen

Turkish Journal of Electrical Engineering and Computer Sciences

Extracting surface orientation and surface depth from one or more images is one of the classic problems in computer vision. Shape-from-shading (SFS) deals with the recovery of 3-D shape from a single shaded image. The shape is recovered by minimizing an energy functional involving constraints such as smoothness. In this constrained problem, although the smoothness constraint helps to stabilize the minimization process, it pushes the reconstruction toward a smooth surface. In this paper, we present a new adaptive shape-from-shading method which reduces this oversmoothing by controlling the smoothness spatially over the image space. In order to improve the quality of …

Arbitrary Views Of High-Dimensional Space And Data, Andrew Ellerton

Theses : Honours

Computer generated images of three dimensional scenes objects are the result of parallel/perspective projections of the objects onto a two dimensional plane. The computational techniques may be extended to project n-dimensional hyperobjects onto (n-1) dimensions, for n > 3. Projection to one less dimension may be applied recursively for data of any high dimension until that data is two-dimensional, when it may be directed to a computer screen or to some other two-dimensional output device. Arbitrary specification of eye location, target location, field-of-view angles and other parameters provide flexibility, so that data may be viewed-and hence perceived-in previously unavailable ways. However, …

Preprocessing Of Microcirculatory Images., Mohamed S. Mansour

Electronic Theses and Dissertations

This thesis project consists of the development of a computerized image processing system to preprocess microvascular images of the mouse Latisimus Dorsi Muscle (LDM). This research has been conducted in association with the Division of Plastic and Reconstructive Surgery at the University of Louisville. The input to the system is a set of 35 or more overlapping microscopic fields or sub_images containing segments of the LDM microcirculation, the output is an adjacent single montage encompassing the entire LDM microvasculature. The developed system presents practical solutions to the problems of image registration, overlap resolution, and image segmentation, in addition, the results …

Real Time Texture Analysis From The Parallel Computation Of Fractal Dimension, Halford I. Hayes Jr.

Computer Science Theses & Dissertations

The discrimination of texture features in an image has many important applications: from detection of man-made objects from a surrounding natural background to identification of cancerous from healthy tissue in X-ray imagery. The fractal structure in an image has been used with success to identify these features but requires unacceptable processing time if executed sequentially.

The paradigm of data parallelism is presented as the best method for applying massively parallel processing to the computation of fractal dimension of an image. With this methodology, and sufficient numbers of processors, this computation can reach real time speeds necessary for many applications. A …