Ship Detection and Segmentation using Image Correlation

There have been intensive research interests in ship detection and segmentation due to high demands on a wide range of civil applications in the last two decades. However, existing approaches, which are mainly based on statistical properties of images, fail to detect smaller ships and boats. Specifically, known techniques are not robust enough in view of inevitable small geometric and photometric changes in images consisting of ships. In this paper a novel approach for ship detection is proposed based on correlation of maritime images. The idea comes from the observation that a fine pattern of the sea surface changes considerably from time to time whereas the ship appearance basically keeps unchanged. We want to examine whether the images have a common unaltered part, a ship in this case. To this end, we developed a method - Focused Correlation (FC) to achieve robustness to geometric distortions of the image content. Various experiments have been conducted to evaluate the effectiveness of the proposed approach.Comment: 8 pages, to be published in proc. of conference IEEE SMC 201

Exploring the Restorative Effects of Nature: Testing A Proposed Visuospatial Theory

In this thesis, the restorative effects of exposure to nature are examined through the lens of existing restoration theories. Limitations of existing theories, such as Attention Restoration Theory and Psycho-evolutionary Restoration Theory, are highlighted. To address the limitations of existing theories, an expanded theoretical framework is proposed: The expanded framework introduces a newly proposed neural mechanism and theory of restoration that build on existing theories by proposing a link to recently discovered reward systems in the ventral visual pathway. Results from six experiments provide consistent evidence to suggest that positive and negative responses to visual scenes are related to the low-level visuospatial properties of the scenes. Specifically, a discovery is made to suggest that the power of a limited visual spatial frequency range can consistently predict responses to natural, urban, and abstract scenes on measures of restoration (blink-rates, number of fixations, self-reported stress and pleasantness). This provides the first evidence to suggest that low-level visual properties of scenes may play an important role in affective and physiological responses to scenes. Furthermore, this newly discovered relationship provides a new way to objectively predict the relative restorative value of any given scene.1 yea