We address the problem of automatically learning object models for recognition and pose
estimation. In contrast to the traditional approach, we formulate the recognition problem as …

We address the problem of automatically learning object models for recognition and pose
estimation. In contrast to the traditional approach, we formulate the recognition problem as …

We address the problem of automatically learning object models for recognition and pose
estimation. In contrast to the traditional approach, we formulate the recognition problem as …

We address the problem of automatically learning object models for recognition and pose
estimation. In contrast to the traditional approach, the recognition problem is formulated here …

The problem of automatically learning object models for recognition and pose estimation is
addressed. In contrast to the traditional approach, the recognition problem is formulated as …

In contrast to the traditional approach, the recognition problem is formulated as one of
matching appearance rather than shape. For any given vision task, all possible appearance …

We consider learning models for object recognition from examples. Our method is motivated
by systems that use the Hausdorff distance as a shape comparison measure. Typically an …

Appearance matching was recently demonstrated as a robust and efficient approach to 3D
object recognition and pose estimation. Each object is represented as a continuous …

Realistic representation of objects requires models which can synthesize the image of an
object under all possible viewing conditions. We propose to learn these models from …

This paper proposes a novel method to detect three-dimensional objects in arbitrary poses
and sizes from a complex image and simultaneously measure their poses and sizes. We …