Deep neural networks (DNNs), which are based loosely on the ventral stream pathway of the primate visual system, are good models of the visual system …
Crowdsourced training data has become a mainstay in computer vision. Some of the most significant discoveries of the last few years were made possible by …
The problem of detecting changes in images taken by a stationary camera has been well studied and many algorithms now exist which perform robustly in …
Human communication is naturally multimodal. On the web, images frequently appear alongside text: for example, product images and descriptions on shopping websites, or social media …
This thesis develops novel algorithms to automate video analysis for fixed monocular surveillance cameras. Specifically, change detection algorithms are proposed to identify spatio-temporal locations in …
Advancements in machine learning techniques have encouraged scholars to focus on convolutional neural network (CNN) based solutions for object detection and pose estimation tasks. Most …
Vehicle surveillance is the task of measuring moving road vehicles to automatically obtain information about vehicle shape, appearance, identity, path of motion, and, ultimately, driver …
Obtaining accurate markerless 3D pose estimations of subjects is an important problem in neuroscience and other fields. Recent work has employed CNNs very successfully to …
Many applications in Computer Vision and Machine Learning entail learning from partially annotated data. A popular family of models that can capture unobserved variables in …
This thesis develops the multiple view geometry of arbitrary, piecewise differentiable curves using differential geometry, and the beginnings of a theory on general surfaces. These …
We propose a new paradigm for vision-based human motion capture. This paradigm extends the traditional capture of poses by providing guarantees of physical plausibility for …
This thesis is concerned with estimating the time-varying 3-d surface geometry and surface appearance of dynamic scenes from images. An accurate reconstruction of a 4-d …
Normalized cross-correlation (NCC) is a powerful matching tool used for finding corresponding features between two signals. In computer vision applications, NCC can be used to …
One of the major challenges in computer vision is generic object recognition, which aims to delineate and identify the category of every object in an …
Thanks to the recent advances in computer science and engineering, computational algorithms to solve digitized jigsaw puzzles have been developed to assist people in assembling …
This thesis is a mathematical and computational study of compositional vision. Three topics are covered: (1) ROC performance in a compositional world; (2) the construction …
Statistical models of non-rigid deformable shape have wide application in many fields, including computer vision, computer graphics, and biometry. We show that shape deformations are …
The study of shapes and their similarities is central in computer vision, in that it allows to recognize and classify objects from their representation. One …
