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The human eye is able to locate objects or regions of importance in its field of vision. Many visual saliency models have been proposed to replicate the human visual system (HVS) in detecting salient objects in a visual scene. A colour space transformation from the RGB space is assumed to increase the detection performance, given the reason that the transformed colour space would allow a better representation...
Simultaneous patterns within images may have conflicting interpretations depending on context (other representations concurrently inferred). This causes significant problems known as dasiathe binding problempsila and dasiathe superposition catastrophepsila for recognition algorithms that incorporate parameter optimization (including neural networks). Previously oscillatory dynamics have been proposed...
In this paper we address the problem of localisation and recognition of human activities in unsegmented image sequences. The main contribution of the proposed method is the use of an implicit representation of the spatiotemporal shape of the activity which relies on the spatiotemporal localization of characteristic, sparse, dasiavisual wordspsila and dasiavisual verbspsila. Evidence for the spatiotemporal...
To understand video affective content automatically, the primary task is to transform the abstract concept of emotion into the form which can be handled by the computer easily. An improved V-A emotion space is proposed to address this problem. It unifies the discrete and dimensional emotion model by introducing the typical fuzzy emotion subspace. Fuzzy C-mean clustering (FCM) algorithm is adopted...
Image parsing remains difficult due to the need to combine local and contextual information when labeling a scene. We approach this problem by using the epitome as a prior over label configurations. Several properties make it suited to this task. First, it allows a condensed patch-based representation. Second, efficient E-M based learning and inference algorithms can be used. Third, non-stationarity...
A novel signal source separation method is introduced for analysis of intrinsic Optical Imaging (OI) and functional Magnetic Resonance Imaging (fMRI) data. This method is based on the fact that all real interesting signals are autocorrelated spatially as well as temporally. Many signal source separation algorithms which using autocorrelation or other structure information of the interesting signals,...
In this paper, we present a one dimensional descriptor for the two dimensional object silhouettes associated with each level of barycenter contour for multiple views shape matching and retrieval. Firstly, the barycenter contour is applied onto the shape contour. Then the averaging multi-triangle area representation (AMTAR) at each level of barycenter contour is computed as the shape descriptor. Finally,...
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