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Image search with LSH and shape context
(University of Missouri--Columbia, 2016)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Partial-duplicate image search is a problem of searching the query image cropped from the same original image from a large database. Kd-tree have a ...
Pixel level pavement crack detection using deep convolutional neural network with residual blocks
(University of Missouri--Columbia, 2019)
Road condition monitoring, such as surface defects and pavement cracks detection, is an important task in road management. Automated road surface defect detection is also a challenging problem in computer vision and machine ...
Moving objects detection and labeling in surveillance videos
(University of Missouri--Columbia, 2014)
Moving objects detection and labeling are an important component of intelligent surveillance systems. Accurate classification of moving objects allows the monitoring system to react to certain events of interest. In this ...
Performance analysis of mix-kernel convolutional neural network
(University of Missouri--Columbia, 2016)
Deep convolutional neural networks (DCNN) have achieved the state-of-the-art performance in a number of computer vision tasks in recent years, including object detection, classification and recognition. The DCNN is very ...
Robust person tracking in indoor environments
(University of Missouri--Columbia, 2014)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.]
Person re-identification with pairwise learning and ranking
(University of Missouri--Columbia, 2014)
Stock market forecasting using recurrent neural network
(University of Missouri--Columbia, 2016)
In this research, we study the problem of stock market forecasting using Recurrent Neural Network(RNN) with Long Short-Term Memory (LSTM). The purpose of this research is to examine the feasibility and performance of LSTM ...
Distributed resource allocation and performance optimization for video communication over mesh networks based on swarm intelligence
(University of Missouri--Columbia, 2007)
Mesh networking technologies allow a system of communication devices to communicate with each other over a dynamic and self-organizing wired or wireless network from everywhere at anytime. Large-scale mesh communication ...
Transmission distortion modeling for wireless video communication
(University of Missouri--Columbia, 2005)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] A major challenge in video wireless communication is that the channel is time-varying and error-prone. The lost video packet and the packet received ...
Optimal video sensing strategy and performance analysis for wireless video sensors under delay constraints
(University of Missouri--Columbia, 2005)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] A wireless sensor network (WSN) is a system of spatially distributed sensors that capture, process and transmit information over a mobile wireless ...
Robust motion estimation techniques
(University of Missouri--Columbia, 2007)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Motion estimation is a very important step in many video processing tasks, including video compression, object tracking, and etc. A video may experience ...
Efficient H.264 video coding with a working memory of objects
(University of Missouri--Columbia, 2009)
Efficient spatiotemporal prediction to remove the source redundancy is critical in video coding. The newest international standard H.264 video coding introduces several advanced features, such as multiple-frame motion ...
Embedded system design and power-rate-distortion optimization for video encoding under energy constraints
(University of Missouri--Columbia, 2007)
The portable devices used in video communication application are powered by batteries. Video encoding schemes, however, are often computationally intensive and energy-demanding, even after being fully optimized with existing ...
Automated video processing and scene understanding for intelligent video surveillance
(University of Missouri--Columbia, 2010)
Recent advances in key technologies have enabled the deployment of surveillance video cameras on various platforms. There is an urgent need to develop advanced computational methods and tools for automated video processing ...
Vehicle license plate detection and recognition
(University of Missouri--Columbia, 2010)
In this work, we develop a license plate detection and recognition method using a SVM (Support Vector Machine) classifier with HOG (Histogram of Oriented Gradients) features. The system performs window searching at different ...
Significance-linked connected component analysis+ for wavelet image coding
(University of Missouri--Columbia, 2010)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] The Significance-Linked Connected Component Analysis+ (SLCCA+) is a efficient wavelet image coding algorithm that extends SLCCA by using new data ...
Frame interpolation in H.264
(University of Missouri--Columbia, 2010)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] In video transmission over low-bandwidth networks, videos are often encoded at low frame rates. At the decoder side, frame interpolation is often ...
Vehicle license plate detection and recognition
(University of Missouri--Columbia, 2013)
In this work, we develop a license plate detection method using a SVM (Support Vector Machine) classifier with HOG (Histogram of Oriented Gradients) features. The system performs window searching at different scales and ...
Pedestrian detection and counting in surveillance videos
(University of Missouri--Columbia, 2013)
Pedestrian detection and counting have important application in video surveillance for entrance monitoring, customer behavior analysis, and public service management. In this thesis, we propose an accurate, reliable and ...
Ensemble video object cut in highly dynamic scenes
(University of Missouri--Columbia, 2014)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] We consider video object cut as an ensemble of framelevel background-foreground object classifiers which fuses information across frames and refine ...