Indexing with Unknown Illumination and Pose

Ira Kemelmacher                   Ronen Basri

Weizmann Institute of Science

Abstract: The task of identifying 3D objects in 2D images is difficult due to variation in objects’ appearance with changes in pose and lighting. The task is further complicated by the presence of occlusion and clutter. Shape indexing is a method for rapid association between features identified in an image and their corresponding 3D features stored in a database. Previous indexing methods ignored variations due to lighting, restricting the approach to polyhedral objects. In this paper, we further develop these methods to handle variations in both pose and lighting. We focus on rigid objects undergoing a scaled-orthographic projection and use spherical harmonics to represent lighting. The resulting integrated algorithm can recognize 3D objects from a single input image; furthermore, it recovers the pose and lighting of each familiar object in the given image. The algorithm has been tested on a database of real objects, demonstrating its performance on cluttered scenes under a variety of poses and illumination conditions.

Keywords: indexing, identification of 3D objects, arbitrary lighting, arbitrary pose, single images, recognition of familiar objects.

For each result we present the input image, image with image points used painted in colors to indicate the models they have voted for where large concentrations of points that vote for the correct model are seen in regions where an object appears, and the output  image with winning objects rendered under the recovered lighting and poses.

Indoor scene:

Outdoor scene:

Night scene:


CVPR'05 Paper: [PDF]

3D laser scans database: [webpage]

Presentation: [PPT] [PDF]


author = {"Ira Kemelmacher and Ronen Basri"},
title = {"Indexing with Unknown Illumination and Pose."},
journal = {"IEEE Conference on Computer Vision and Pattern Recognition"},
year = {"2005"}
pages = {"909--916"}

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Last updated on July 5, 2005