Data processing: measuring – calibrating – or testing – Measurement system – Statistical measurement
Reexamination Certificate
2005-04-19
2005-04-19
Barlow, John (Department: 2863)
Data processing: measuring, calibrating, or testing
Measurement system
Statistical measurement
C342S064000, C706S016000, C706S052000
Reexamination Certificate
active
06882959
ABSTRACT:
A system and process for tracking an object state over time using particle filter sensor fusion and a plurality of logical sensor modules is presented. This new fusion framework combines both the bottom-up and top-down approaches to sensor fusion to probabilistically fuse multiple sensing modalities. At the lower level, individual vision and audio trackers can be designed to generate effective proposals for the fuser. At the higher level, the fuser performs reliable tracking by verifying hypotheses over multiple likelihood models from multiple cues. Different from the traditional fusion algorithms, the present framework is a closed-loop system where the fuser and trackers coordinate their tracking information. Furthermore, to handle non-stationary situations, the present framework evaluates the performance of the individual trackers and dynamically updates their object states. A real-time speaker tracking system based on the proposed framework is feasible by fusing object contour, color and sound source location.
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Chen Yunqiang
Rui Yong
Barlow John
Le John
Lyon Richard T.
Lyon & Harr LLP
Microsoft Corporation
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