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Full-Text Articles in Engineering
A Study Of Localization And Latency Reduction For Action Recognition, Syed Zain Masood
A Study Of Localization And Latency Reduction For Action Recognition, Syed Zain Masood
Electronic Theses and Dissertations
The success of recognizing periodic actions in single-person-simple-background datasets, such as Weizmann and KTH, has created a need for more complex datasets to push the performance of action recognition systems. In this work, we create a new synthetic action dataset and use it to highlight weaknesses in current recognition systems. Experiments show that introducing background complexity to action video sequences causes a significant degradation in recognition performance. Moreover, this degradation cannot be fixed by fine-tuning system parameters or by selecting better feature points. Instead, we show that the problem lies in the spatio-temporal cuboid volume extracted from the interest point …
Gradient Based Mrf Learning For Image Restoration And Segmentation, Kegan Samuel
Gradient Based Mrf Learning For Image Restoration And Segmentation, Kegan Samuel
Electronic Theses and Dissertations
The undirected graphical model or Markov Random Field (MRF) is one of the more popular models used in computer vision and is the type of model with which this work is concerned. Models based on these methods have proven to be particularly useful in low-level vision systems and have led to state-of-the-art results for MRF-based systems. The research presented will describe a new discriminative training algorithm and its implementation. The MRF model will be trained by optimizing its parameters so that the minimum energy solution of the model is as similar as possible to the ground-truth. While previous work has …
Markerless Tracking Using Polar Correlation Of Camera Optical Flow, Prince Gupta
Markerless Tracking Using Polar Correlation Of Camera Optical Flow, Prince Gupta
Electronic Theses and Dissertations
We present a novel, real-time, markerless vision-based tracking system, employing a rigid orthogonal configuration of two pairs of opposing cameras. Our system uses optical flow over sparse features to overcome the limitation of vision-based systems that require markers or a pre-loaded model of the physical environment. We show how opposing cameras enable cancellation of common components of optical flow leading to an efficient tracking algorithm that captures five degrees of freedom including direction of translation and angular velocity. Experiments comparing our device with an electromagnetic tracker show that its average tracking accuracy is 80% over 185 frames, and it is …
Spatio-Temporal Maximum Average Correlation Height Templates In Action Recognition And Video Summarization, Mikel Rodriguez
Spatio-Temporal Maximum Average Correlation Height Templates In Action Recognition And Video Summarization, Mikel Rodriguez
Electronic Theses and Dissertations
Action recognition represents one of the most difficult problems in computer vision given that it embodies the combination of several uncertain attributes, such as the subtle variability associated with individual human behavior and the challenges that come with viewpoint variations, scale changes and different temporal extents. Nevertheless, action recognition solutions are critical in a great number of domains, such video surveillance, assisted living environments, video search, interfaces, and virtual reality. In this dissertation, we investigate template-based action recognition algorithms that can incorporate the information contained in a set of training examples, and we explore how these algorithms perform in action …
Multi-View Approaches To Tracking, 3d Reconstruction And Object Class Detection, Saad Khan
Multi-View Approaches To Tracking, 3d Reconstruction And Object Class Detection, Saad Khan
Electronic Theses and Dissertations
Multi-camera systems are becoming ubiquitous and have found application in a variety of domains including surveillance, immersive visualization, sports entertainment and movie special effects amongst others. From a computer vision perspective, the challenging task is how to most efficiently fuse information from multiple views in the absence of detailed calibration information and a minimum of human intervention. This thesis presents a new approach to fuse foreground likelihood information from multiple views onto a reference view without explicit processing in 3D space, thereby circumventing the need for complete calibration. Our approach uses a homographic occupancy constraint (HOC), which states that if …
Detecting Curved Objects Against Cluttered Backgrounds, Jan Prokaj
Detecting Curved Objects Against Cluttered Backgrounds, Jan Prokaj
Electronic Theses and Dissertations
Detecting curved objects against cluttered backgrounds is a hard problem in computer vision. We present new low-level and mid-level features to function in these environments. The low-level features are fast to compute, because they employ an integral image approach, which makes them especially useful in real-time applications. The mid-level features are built from low-level features, and are optimized for curved object detection. The usefulness of these features is tested by designing an object detection algorithm using these features. Object detection is accomplished by transforming the mid-level features into weak classifiers, which then produce a strong classifier using AdaBoost. The resulting …
Towards A Self-Calibrating Video Camera Network For Content Analysis And Forensics, Imran Junejo
Towards A Self-Calibrating Video Camera Network For Content Analysis And Forensics, Imran Junejo
Electronic Theses and Dissertations
Due to growing security concerns, video surveillance and monitoring has received an immense attention from both federal agencies and private firms. The main concern is that a single camera, even if allowed to rotate or translate, is not sufficient to cover a large area for video surveillance. A more general solution with wide range of applications is to allow the deployed cameras to have a non-overlapping field of view (FoV) and to, if possible, allow these cameras to move freely in 3D space. This thesis addresses the issue of how cameras in such a network can be calibrated and how …
Depth From Defocused Motion, Zarina Myles
Depth From Defocused Motion, Zarina Myles
Electronic Theses and Dissertations
Motion in depth and/or zooming causes defocus blur. This work presents a solution to the problem of using defocus blur and optical flow information to compute depth at points that defocus when they move. We first formulate a novel algorithm which recovers defocus blur and affine parameters simultaneously. Next we formulate a novel relationship (the blur-depth relationship) between defocus blur, relative object depth and three parameters based on camera motion and intrinsic camera parameters. We can handle the situation where a single image has points which have defocused, got sharper or are focally unperturbed. Moreover, our formulation is valid regardless …