Abstract
We present the Incremental Focus of Attention (IFA) architecture for adding robustness to software-based, real-time, motion trackers. The framework provides a structure which, when given the entire camera image to search, efficiently focuses the attention of the system into a narrow set of possible states that includes the target state. IFA offers a means for automatic tracking initialization and reinitialization when environmental conditions momentarily deteriorate and cause the system to lose track of its target. Systems based on the framework degrade gracefully as various assumptions about the environment are violated. In particular, multiple tracking algorithms are layered so that the failure of a single algorithm causes another algorithm of less precision to take over, thereby allowing the system to return approximate feature state information.
Original language | English (US) |
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Pages (from-to) | 189-195 |
Number of pages | 7 |
Journal | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
State | Published - Jan 1 1996 |
Externally published | Yes |
Event | Proceedings of the 1996 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - San Francisco, CA, USA Duration: Jun 18 1996 → Jun 20 1996 |
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition