University of Waterloo

Category: Grid Seams: A fast superpixel algorithm for real-time applications

  • Zahra Gharaee

    Zahra Gharaee

    As a seasoned senior research scientist, I bring expertise in computer vision, machine learning, and artificial intelligence to the forefront of my work. My research endeavours centre around pioneering subjects, including advanced image processing and video analysis, representation learning, action recognition, autonomous systems and graph convolutional neural networks. GoogleScholar LinkedIn ORCiD Github

  • Linlin Xu

    Linlin Xu

    I am a post-doc in Vision and Image Processing Lab, working with professors David Clausi, Alexander Wong on machine learning, intelligent remote sensing analytics and environmental monitoring.

  • Linlin Xu

    Linlin Xu

    I am a Research Assistant Professor in Vision and Image Processing Lab, working on AI, machine learning, Earth Observation and Environmental Remote Sensing projects.

  • Parthipan Siva

    Parthipan Siva

    My research interests are primarily in the field of computer vision and pattern recognition with a focus on video analytics. I am particularly interesting in action/activity recognition in videos using a weakly supervised approach.

  • Grid Seams: A fast superpixel algorithm for real-time applications

    Grid Seams: A fast superpixel algorithm for real-time applications

    Grid Seams is a novel seam carving approach to superpixel generation that preserves image structure information while enforcing a global spatial constraint in the form of a grid structure cost. The seam based approach allows us to obtain superpixels faster than all existing methods while maintaining a high image representation accuracy. Furthermore, our approach allows…

  • Alexander Wong

    Alexander Wong

    My research interests lie in the field of artificial intelligence and computational imaging, with a focus on scalable and explainable deep learning and computational biomedical imaging systems.