Abstract
We present an approach to the recognition of complex-shaped objects in cluttered environments based on edge cues. We first use example images of the desired object in typical backgrounds to train a classifier cascade which determines whether edge pixels in an image belong to an instance of the object or the clutter. Presented with a novel image, we use the cascade to discard clutter edge pixels. The features used for this classification are localized, sparse edge density operations. Experiments validate the effectiveness of the technique for recognition of complex objects in cluttered indoor scenes under arbitrary out-of-image-plane rotation.
| Original language | English (US) |
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| Title of host publication | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
| Volume | 2 |
| State | Published - 2003 |
| Externally published | Yes |
| Event | 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Madison, WI, United States Duration: Jun 18 2003 → Jun 20 2003 |
Other
| Other | 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
|---|---|
| Country | United States |
| City | Madison, WI |
| Period | 6/18/03 → 6/20/03 |
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition
- Software
- Control and Systems Engineering