Viewpoint selection for visual search

Searching for an object in a cluttered area is often complicated by the fact that the clutter hides portions of the area from view. Multiple viewpoints are often required. Previous viewpoint selection algorithms rely on models that represent the portions already viewed. Unfortunately, these models are often difficult to construct when the sensor position is imprecisely known and when the obtainable depth data is sparse. This paper questions whether scene models are really necessary for selecting viewpoints for search tasks. It investigates two alternative viewpoint selection methods that do not rely on such models. One constructs no representation and simply uses a fitted set of viewpoints, while the other selects viewpoints based on detected occluding edges. On average, both model-free methods compare very favorably to model-based methods, although additional work is necessary to ensure that they abort in a timely manner when the desired object cannot be found