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Full-Text Articles in Engineering

Computer Vision-Based Structural Assessment Exploiting Large Volumes Of Images, Chul Min Yeum Dec 2016

Computer Vision-Based Structural Assessment Exploiting Large Volumes Of Images, Chul Min Yeum

Open Access Dissertations

Visual assessment is a process to understand the state of a structure based on evaluations originating from visual information. Recent advances in computer vision to explore new sensors, sensing platforms and high-performance computing have shed light on the potential for vision-based visual assessment in civil engineering structures. The use of low-cost, high-resolution visual sensors in conjunction with mobile and aerial platforms can overcome spatial and temporal limitations typically associated with other forms of sensing in civil structures. Also, GPU-accelerated and parallel computing offer unprecedented speed and performance, accelerating processing the collected visual data. However, despite the enormous endeavor in past ...


Visual Clutter Study For Pedestrian Using Large Scale Naturalistic Driving Data, Kai Yang Aug 2016

Visual Clutter Study For Pedestrian Using Large Scale Naturalistic Driving Data, Kai Yang

Open Access Dissertations

Some of the pedestrian crashes are due to driver’s late or difficult perception of pedestrian’s appearance. Recognition of pedestrians during driving is a complex cognitive activity. Visual clutter analysis can be used to study the factors that affect human visual search efficiency and help design advanced driver assistant system for better decision making and user experience. In this thesis, we propose the pedestrian perception evaluation model which can quantitatively analyze the pedestrian perception difficulty using naturalistic driving data. An efficient detection framework was developed to locate pedestrians within large scale naturalistic driving data. Visual clutter analysis was used ...


Learning In Vision And Robotics, Daniel P. Barrett Apr 2016

Learning In Vision And Robotics, Daniel P. Barrett

Open Access Dissertations

I present my work on learning from video and robotic input. This is an important problem, with numerous potential applications. The use of machine learning makes it possible to obtain models which can handle noise and variation without explicitly programming them. It also raises the possibility of robots which can interact more seamlessly with humans rather than only exhibiting hard-coded behaviors. I will present my work in two areas: video action recognition, and robot navigation. First, I present a video action recognition method which represents actions in video by sequences of retinotopic appearance and motion detectors, learns such models automatically ...


Grounding Robot Motion In Natural Language And Visual Perception, Scott Alan Bronkowski Apr 2016

Grounding Robot Motion In Natural Language And Visual Perception, Scott Alan Bronkowski

Open Access Dissertations

The current state of the art in military and first responder ground robots involves heavy physical and cognitive burdens on the human operator while taking little to no advantage of the potential autonomy of robotic technology. The robots currently in use are rugged remote-controlled vehicles. Their interaction modalities, usually utilizing a game controller connected to a computer, require a dedicated operator who has limited capacity for other tasks.

I present research which aims to ease these burdens by incorporating multiple modes of robotic sensing into a system which allows humans to interact with robots through a natural-language interface. I conduct ...


Reasoning Across Language And Vision In Machines And Humans, Andrei Barbu Oct 2013

Reasoning Across Language And Vision In Machines And Humans, Andrei Barbu

Open Access Dissertations

Humans not only outperform AI and computer-vision systems, but use an unknown computational mechanism to perform tasks for which no suitable approaches exist. I present work investigating both novel tasks and how humans approach them in the context of computer vision and linguistics. I demonstrate a system which, like children, acquires high-level linguistic knowledge about the world. Robots learn to play physically-instantiated board games and use that knowledge to engage in physical play. To further integrate language and vision I develop an approach which produces rich sentential descriptions of events depicted in videos. I then show how to simultaneously detect ...