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Full-Text Articles in Engineering
An Efficient Feature Descriptor And Its Real-Time Applications, Alok Desai
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 …
Vision Based Multiple Target Tracking Using Recursive Ransac, Kyle Ingersoll
Vision Based Multiple Target Tracking Using Recursive Ransac, Kyle Ingersoll
Theses and Dissertations
In this thesis, the Recursive-Random Sample Consensus (R-RANSAC) multiple target tracking (MTT) algorithm is further developed and applied to video taken from static platforms. Development of R-RANSAC is primarily focused in three areas: data association, the ability to track maneuvering objects, and track management. The probabilistic data association (PDA) filter performs very well in the R-RANSAC framework and adds minimal computation cost over less sophisticated methods. The interacting multiple models (IMM) filter as well as higher-order linear models are incorporated into R-RANSAC to improve tracking of highly maneuverable targets. An effective track labeling system, a more intuitive track merging criteria, …
The Application And Accuracy Of Structure From Motion Computer Vision Models With Full-Scale Geotechnical Field Tests, L. Palmer, Kevin W. Franke, R. Abraham Martin, B. E. Sines, Kyle M. Rollins, John Hedengren
The Application And Accuracy Of Structure From Motion Computer Vision Models With Full-Scale Geotechnical Field Tests, L. Palmer, Kevin W. Franke, R. Abraham Martin, B. E. Sines, Kyle M. Rollins, John Hedengren
Faculty Publications
Structure from motion (SfM) computer vision is a relatively new technology that allows engineers to reconstruct a three-dimensional (3D) model of a given scene using twodimensional digital photographs captured from a single, moving camera. SfM computer vision provides an economic and user-friendly alternative to other 3D scene-capture and modeling tools such as light distance and ranging (LiDAR). Although the resolution and accuracy of laser-based modeling methods are generally superior to vision-based modeling methods, the economic advantages associated with the latter may make it a useful and practical alternative for many geotechnical engineering applications. Although other engineering disciplines have investigated the …