Depth estimation from image structure

被引:230
作者
Torralba, A
Oliva, A
机构
[1] MIT, Artif Intelligence Lab, Cambridge, MA 02139 USA
[2] Brigham & Womens Hosp, Ctr Ophthalm Res, Boston, MA 02115 USA
关键词
depth; image statistics; scene structure; scene recognition; scale selection; monocular vision;
D O I
10.1109/TPAMI.2002.1033214
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In 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 provide information about the actual "scale" of the space. One possible source of information for absolute depth estimation is the image size of known objects. However, object recognition, under unconstrained conditions, remains difficult and unreliable for current computational approaches. Here, we propose a source of information for absolute depth estimation based on the whole scene structure that does not rely on specific objects. 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.
引用
收藏
页码:1226 / 1238
页数:13
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