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  • An integrated framework for combining gist vision with object segregation categorisation and recognition
    Publication . Rodrigues, J. M. F.; Almeida, D.; Martins, Jaime; Lam, Roberto
    There are roughly two processing systems: (1) very fast gist vision of entire scenes, completely bottom-up and data driven, and (2) Focus-of-Attention (FoA) with sequential screening of specific image regions and objects. The latter system has to be sequential because unnormalised input objects must be matched against normalised templates of canonical object views stored in memory, which involves dynamic routing of features in the visual pathways.
  • Cortical multiscale line-edge disparity model
    Publication . Rodrigues, J. M. F.; Martins, Jaime; Lam, Roberto; du Buf, J. M. H.
    Most biological approaches to disparity extraction rely on the disparity energy model (DEM). In this paper we present an alternative approach which can complement the DEM model. This approach is based on the multiscale coding of lines and edges, because surface structures are composed of lines and edges and contours of objects often cause edges against their background. We show that the line/edge approach can be used to create a 3D wireframe representation of a scene and the objects therein. It can also significantly improve the accuracy of the DEM model, such that our biological models can compete with some state-of-the-art algorithms from computer vision.
  • Region segregation and saliency using colour information
    Publication . Martins, Jaime; Rodrigues, J. M. F.; du Buf, J. M. H.
    Saliency maps determine the likelihood that we focus on interesting areas of scenes or images. These maps can be built using several low-level image features, one of which having a particular relevance: colour. In this paper we present a new computational model, based only on colour features, which provides a sound basis for saliency maps for static images and video, plus region segregation and cues for local gist vision.
  • Biological models for active vision: towards a unified architecture
    Publication . Terzic, Kasim; Lobato, D.; Saleiro, Mário; Martins, Jaime; Farrajota, Miguel; Rodrigues, J. M. F.; du Buf, J. M. H.
    Building a general-purpose, real-time active vision system completely based on biological models is a great challenge. We apply a number of biologically plausible algorithms which address different aspects of vision, such as edge and keypoint detection, feature extraction,optical flow and disparity, shape detection, object recognition and scene modelling into a complete system. We present some of the experiments from our ongoing work, where our system leverages a combination of algorithms to solve complex tasks.
  • Disparity energy model using a trained neuronal population
    Publication . Martins, Jaime; Rodrigues, J. M. F.; du Buf, J. M. H.
    Depth information using the biological Disparity Energy Model can be obtained by using a population of complex cells. This model explicitly involves cell parameters like their spatial frequency, orientation, binocular phase and position difference. However, this is a mathematical model. Our brain does not have access to such parameters, it can only exploit responses. Therefore, we use a new model for encoding disparity information implicitly by employing a trained binocular neuronal population. This model allows to decode disparity information in a way similar to how our visual system could have developed this ability, during evolution, in order to accurately estimate disparity of entire scenes