Allan Hanbury

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Images can affect people on an emotional level. Since the emotions that arise in the viewer of an image are highly subjective, they are rarely indexed. However there are situations when it would be helpful if images could be retrieved based on their emotional content. We investigate and develop methods to extract and combine low-level features that(More)
We focus on the detection of orthogonal vanishing points using line segments extracted from a single view, and using these for camera self-calibration. Recent methods view this problem as a two-stage process. Vanishing points are extracted through line segment clustering and subsequently likely orthogonal candidates are selected for calibration.(More)
In order to evaluate automated image annotation and object recognition algorithms, ground truth in the form of a set of images correctly annotated with text describing each image is required. In this paper, three image annotation approaches are reviewed: free text annotation, keyword annotation and annotation based on ontologies. The practical aspects of(More)
The processing and analysis of colour images has become an important area of study and application. The representation of the RGB colour space in 3D-polar coordinates (hue, saturation and brightness) can sometimes simplify this task by revealing characteristics not visible in the rectangular coordinate representation. The literature describes many such(More)
This paper presents the results of task 3 of the ShARe/CLEF eHealth Evaluation Lab 2014. This evaluation lab focuses on improving access to medical information on the web. The task objective was to investigate the effect of using additional information such as a related discharge summary and external resources such as medical ontologies on the effectiveness(More)
We investigate the use of the standard morphological texture characterisation methods, the granulometry and the variogram, in the task of texture classification. These methods are applied to both colour and greyscale texture images. We also introduce a method for minimising the effect of different illumination conditions and show that its use leads to(More)
Skin detection is used in applications ranging from face detection, tracking body parts and hand gesture analysis, to retrieval and blocking objectionable content. For robust skin segmentation and detection, we investigate color classification based on random forest. A random forest is a statistical framework with a very high generalization accuracy and(More)