Linear Operator for Object Recognition

Visual object recognition involves the identification of images of 3-D ob(cid: 173) jects seen from arbitrary viewpoints. We suggest an approach to object recognition in which a view is represented as a collection of points given by their location in the image. An object is modeled by a set of 2-D views together with the correspondence between the views. We show that any novel view of the object can be expressed as a linear combination of the stored views. Consequently, we build a linear operator that distinguishes between views of a specific object and views of other objects. This opera(cid: 173) tor can be implemented using neural network architectures with relatively simple structures.

Authors

• Ronen Basri
• Shimon Ullman

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