Doctor of Philosophy (Ph.D.), University of Dayton, 2014, Electrical Engineering

Object detection and tracking in imagery captured by aerial systems are becoming increasingly important in computer vision research. In aerial imagery, objects can appear in any orientation, varying sizes and in different lighting conditions. Due to the exponential growth in sensor technology, increasing size and resolution of aerial imagery are becoming a challenge for real-time computation. A rotation invariant feature extraction technique for detecting and tracking objects in aerial imagery is presented in this dissertation. Rotation invariance in the feature representation is addressed by considering concentric circular regions centered at visually salient locations of the object. The intensity distribution characteristics of the object region are used to represent an object effectively. A set of intensity-based features is derived from intensity histograms of the circular regions and they are inherently rotation invariant. An integral histogram computation approach is used to compute these features efficiently. To improve the representational strength of the feature set for rotation and illumination-invariant object detection, a gradient-based feature set is derived from normalized gradient orientation histograms of concentric regions. Rotation invariance is achieved by considering the magnitude of the Discrete Fourier Transform (DFT) of the gradient orientation histograms. A novel computational framework called Integral DFT is presented for fast and efficient extraction of gradient-based features in large imagery. A part-based model, which relies on a representation of an object as an aggregation of significant parts, using the gradient-based features is also presented in this dissertation. Integrating the features of significant parts gives robustness to partial occlusions and slight deformations, thus leading to a better object representation. The effectiveness of the intensity-based feature is demonstrated in tracking objects in Wide Area Motion Imagery (WA (open full item for complete abstract)

Committee: Vijayan Asari (Committee Chair); Keigo Hirakawa (Committee Member); Raul Ordonez (Committee Member); Youssef Raffoul (Committee Member) Subjects: Computer Engineering; Computer Science; Electrical Engineering; Engineering

Master of Science (M.S.), University of Dayton, 2013, Electrical Engineering

Image registration is a task that has been focused on in many fields that deal with object detection and tracking on video sequences. When tracking any object throughout a scene, more often than not, image registration is used to align video frames to help segment moving objects from the background. With that in mind, a new registration method employing a two stage approach is proposed that efficiently registers aerial imagery. The proposed coarse to fine approach uses a combination of two efficient algorithms: Speeded Up Robust Features (SURF) for the generation of an estimated homography and the Efficient Second-Order Minimization (ESM) for fine tuning the homography generated from the coarse SURF method. Experiments are performed on several different aerial image databases, which vary in both size and resolution. The proposed algorithm proves to be effective and accurate when dealing with the changing databases; however, there are times when registration fails, specifically when very large warping parameters occur between two scenes. When registering consecutive image pairs within a sequence of images, accurate registration is needed to support many of the tracking algorithm's downstream processes. When one or several bad frames are present within a sequence of images, it becomes necessary to exclude these frames from use. A "shot" is a sequence of frames within a video sequence where an object or objects are tracked consistently. In registration terms, it is a sequence of images that have been registered correctly without disrupting the tracks for targets. A shot break occurs when one frame cannot be linked with a transformation homography to another frame within an image sequence. The goal of a shot break detection algorithm is to exclude bad frames from use and detect when shot breaks occur. This thesis implements several internal and external shot break detection algorithms where bad frames and shot breaks are detected within a sequen (open full item for complete abstract)

Committee: Vijayan Asari Ph.D. (Committee Chair); Juan Vasquez Ph.D. (Committee Member); Eric Balster Ph.D. (Committee Member) Subjects: Electrical Engineering; Engineering