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Convolutional Gated Recurrent Networks for Video Segmentation
Mennatullah Siam, Sepehr Valipour, Martin Jagersand +1
Semantic segmentation has recently witnessed major progress, where fully convolutional neural networks have shown to perform well. However, most of the previous work focused on imp…
Unifying Registration based Tracking: A Case Study with Structural Similarity
Abhineet Singh, Mennatullah Siam, Martin Jagersand
This paper adapts a popular image quality measure called structural similarity for high precision registration based tracking while also introducing a simpler and faster variant of…
Parking Stall Vacancy Indicator System Based on Deep Convolutional Neural Networks
Sepehr Valipour, Mennatullah Siam, Eleni Stroulia +1
Parking management systems, and vacancy-indication services in particular, can play a valuable role in reducing traffic and energy waste in large cities. Visual detection methods r…
Recurrent Fully Convolutional Networks for Video Segmentation
Sepehr Valipour, Mennatullah Siam, Martin Jagersand +1
Image segmentation is an important step in most visual tasks. While convolutional neural networks have shown to perform well on single image segmentation, to our knowledge, no stud…
Modular Decomposition and Analysis of Registration based Trackers
Abhineet Singh, Ankush Roy, Xi Zhang +1
This paper presents a new way to study registration based trackers by decomposing them into three constituent sub modules: appearance model, state space model and search method. It…
Modular Tracking Framework: A Unified Approach to Registration based Tracking
Abhineet Singh, Martin Jagersand
This paper presents a modular, extensible and highly efficient open source framework for registration based tracking called Modular Tracking Framework (MTF). Targeted at robotics a…