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Accurate, fast, and robust 3D city-scale reconstruction using wide area motion imagery
(University of Missouri--Columbia, 2021)
Multi-view stereopsis (MVS) is a core problem in computer vision, which takes a set of scene views together with known camera poses, then produces a geometric representation of the underlying 3D model Using 3D reconstruction ...
Single and multi-object video tracking using local and deep architectures
(University of Missouri--Columbia, 2022)
Moving object tracking is a fundamental computer vision task with a wide variety of real-life applications ranging from surveillance and autonomous systems to biomedical video analysis. A robust, accurate, scalable, and ...
Deep learning and DCT-based hand-crafted features for computer vision tasks
(University of Missouri--Columbia, 2022)
Feature extraction and matching are critical components for many computer vision tasks including camera pose estimation, 3D reconstruction, simultaneous localization and mapping (SLAM), and object tracking, etc. Features ...
Deep learning architectures for 2D and 3D scene perception
(University of Missouri--Columbia, 2021)
Scene understanding is a fundamental problem in computer vision tasks, that is being more intensively explored in recent years with the development of deep learning. In this dissertation, we proposed deep learning structures ...