Unposed Object Recognition using an Active Approach
Abstract
Object recognition is a practical problem with a wide variety of potential applications. Recognition becomes substantially more difficult when objects have not been presented in some logical, posed manner selected by a human observer. We propose to solve this problem using active object recognition, where the same object is viewed from multiple viewpoints when it is necessary to gain confidence in the classification decision. We demonstrate the effect of unposed objects on a state-of-the-art approach to object recognition, then show how an active approach can increase accuracy. The active approach works by attaching confidence to recognition, prompting further inspection when confidence is low. We demonstrate a performance increase on a wide variety of objects from the RGB-D database, showing a significant increase in recognition accuracy.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 01, 2013
- Accession Number
- ADA618892
Entities
People
- J. Gregory Trafton
- Wallace Lawson
Organizations
- United States Naval Research Laboratory