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Publication - Professor Walterio Mayol-Cuevas

    High Level Activity Recognition using Low Resolution Wearable Vision


    Sundaram, S & Mayol-Cuevas, W, 2009, ‘High Level Activity Recognition using Low Resolution Wearable Vision’. in: First Workshop on Egocentric Vision, in conjunction with the International Conference on Computer Vision and Pattern Recognition. Institute of Electrical and Electronics Engineers (IEEE)


    This paper presents a system aimed to serve as the enabling platform for a wearable assistant. The method observes manipulations from a wearable camera and classifies activities from roughly stabilized low resolution images (160x120 pixels) with the help of a 3-level Dynamic Bayesian Network and adapted temporal templates. Our motivation is to explore robust but computationally inexpensive visual methods to perform as much activity inference as possible without resorting to more complex object or hand
    detectors. The description of the method and results obtained are presented, as well as the motivation for further work in the area of wearable visual sensing.

    Full details in the University publications repository