Collaborators:
David Jacobs (NECI, USA), Peter Belhumeur (Yale University, USA).
Key words:
Resume:
We consider the problem of recognizing an object from its
silhouette. We focus on the case in which the camera translates, and
rotates about a known axis parallel to the image, such as when a mobile
robot explores an environment. In this case we present an algorithm for
determining whether a new silhouette could come from the same object that
produced two previously seen silhouettes. In a basic case, when
cross-sections of each silhouette are single line segments, we can check
for consistency between three silhouettes using linear programming. This
provides the basis for methods that handle more complex cases. We show
many experiments that demonstrate the performance of these methods when
there is noise, some deviation from the assumptions of the algorithms, and
partial occlusion. Previous work has addressed the problem of precisely
reconstructing an object using many silhouettes taken under controlled
conditions. Our work shows that recognition can be performed without
complete reconstruction, so that a small number of images can be used,
with viewpoints that are only partly constrained.
Publications:
- "Judging Whether Multiple Silhouettes Can Come from the Same
Object", David Jacobs, Peter Belhumeur and Ian H. Jermyn. Proceedings
of the 4th International Workshop on Visual Form, Capri,
Italy, 2001 (Springer-Verlag Lecture Notes in Computer Science 2059). (PDF)
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