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Global Depth Perception from Familiar Scene Structure

dc.date.accessioned2004-10-20T21:04:45Z
dc.date.accessioned2018-11-24T10:23:36Z
dc.date.available2004-10-20T21:04:45Z
dc.date.available2018-11-24T10:23:36Z
dc.date.issued2001-12-01en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/7267
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/7267
dc.description.abstractIn the absence of cues for absolute depth measurements as binocular disparity, motion, or defocus, the absolute distance between the observer and a scene cannot be measured. The interpretation of shading, edges and junctions may provide a 3D model of the scene but it will not inform about the actual "size" of the space. One possible source of information for absolute depth estimation is the image size of known objects. However, this is computationally complex due to the difficulty of the object recognition process. Here we propose a source of information for absolute depth estimation that does not rely on specific objects: we introduce a procedure for absolute depth estimation based on the recognition of the whole scene. The shape of the space of the scene and the structures present in the scene are strongly related to the scale of observation. We demonstrate that, by recognizing the properties of the structures present in the image, we can infer the scale of the scene, and therefore its absolute mean depth. We illustrate the interest in computing the mean depth of the scene with application to scene recognition and object detection.en_US
dc.format.extent22 p.en_US
dc.format.extent40226611 bytes
dc.format.extent7425856 bytes
dc.language.isoen_US
dc.subjectAIen_US
dc.subjectdepthen_US
dc.subjectmonocularen_US
dc.subjectscale selectionen_US
dc.subjectnatural imagesen_US
dc.subjectscene recognitionen_US
dc.titleGlobal Depth Perception from Familiar Scene Structureen_US


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