Towards true 3D object recognition
Towards true 3D object recognition
复制标题
迈向真正的 3D 物体识别
DOI：
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复制
发表时间：
2004
期刊：
影响因子：
--
通讯作者：
C. Schmid
中科院分区：
文献类型：
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作者：
J. Ponce;Svetlana Lazebnik;Fred Rothganger;C. Schmid
本次演讲将讨论在照片和图像序列中识别三维（3D）物体的问题，重新审视视点不变量作为形状和外观的局部表示。关键的见解是，尽管光滑表面在大范围内几乎从不是平面的，因此（通常）不承认全局不变量，但它们在小范围内总是平面的——也就是说，足够小的表面斑块总是可以被认为是由共面点组成的——因此可以用平面不变量局部表示。这是一种新的、统一的对象识别方法的基础，其中对象模型由一组小（平面）补丁、它们的不变量和它们的3D空间关系的描述组成。具体来说，本提议中使用的局部不变量是Lindeberg和Garding以及Mikolajczyk和Schmid最近开发的显著图像特征（“兴趣点”）附近图像亮度模式的仿射不变量描述。这些仿射不变补丁提供了局部物体外观的规范化表示，在视点和光照变化下不变，可以用作图像，部分或物体相似性的局部度量。利用局部不变量之间的空间关系来表示全局目标结构，驱动识别过程。我将用3D对象识别问题的两个基本实例来说明我们的方法：(1)从一小组未注册的图片中建模刚性3D对象，并在从无约束视点拍摄的杂乱照片中识别它们；(2)非刚性变换下非均匀纹理模式的表示、学习和识别。如果时间允许的话，我将简要讨论我们目前在3D摄影中使用形状，纹理和运动线索的工作。
This talk addresses the problem of recognizing three-dimensional (3D) objects in photographs and image sequences, revisiting viewpoint invariants as a -local- representation of shape and appearance. The key insight is that, although smooth surfaces are almost never planar in the large, and thus do not (in general) admit global invariants, they are always planar in the small---that is, sufficiently small surface patches can always be thought of as being comprised of coplanar points---and thus can be represented locally by planar invariants. This is the basis for a new, unified approach to object recognition where object models consist of a collection of small (planar) patches, their invariants, and a description of their 3D spatial relationship. Specifically, the local invariants used in this proposal are the affine-invariant descriptions of the image brightness pattern in the neighborhood of salient image features ("interest points") recently developed by Lindeberg and Garding and by Mikolajczyk and Schmid. These affine-invariant patches provide a normalized representation of the local object appearance, invariant under viewpoint and illumination changes, that can be used as a local measure of image, part, or object similarity. The spatial relationship between local invariants is used to represent the global object structure and drive the recognition process. I will illustrate our approach with two fundamental instances of the 3D object recognition problem: (1) modeling rigid 3D objects from a small set of unregistered pictures and recognizing them in cluttered photographs taken from unconstrained viewpoints; and (2) representing, learning, and recognizing non-uniform texture patterns under non-rigid transformations. If time permits, I will conclude with a brief discussion of our current work in 3D photography using shape, texture, and motion cues.
影响因子：
19.5
作者：
TOMASI, C;KANADE, T
通讯作者：
KANADE, T
基于特征脸的人脸建模与识别
DOI：
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发表时间：
2003
期刊：
IPSJ SIG Technical Reports Vol. CVIM-139
影响因子：
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作者：
T.;Shakunaga;F.;Sakaue;Y.;Matsubara
通讯作者：
Matsubara