Estimating and tracking multiple attributes of multiple objects from multi-sensor data
First Claim
1. A system for estimating and tracking multiple attributes of multiple objects from multi-sensor data, the system comprising:
- an object detector stored in memory and executed by at least one processor to determine multiple probable objects based at least in part on features associated with sensor data, the sensor data representing data captured by at least one of a plurality of sensors, the determination being made in parallel for the features;
a hypothesis generator stored in memory and executed by the at least one processor to form hypotheses based at least in part on associating the features with the multiple probable objects;
a grouping module stored in memory and executed by the at least one processor to attribute the formed hypotheses to channels; and
a tracking module stored in memory and executed by the at least one processor to construct sequences of the formed hypotheses;
the tracking module being configured to provide the channels and constructed sequences for use in signal processing.
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Accused Products
Abstract
Systems and methods for estimating and tracking multiple attributes of multiple objects from multi-sensor data are provided. An exemplary method includes identifying features associated with sensor data. The sensor data represents data captured by at least one of a plurality of acoustic and non-acoustic sensors. Identification of the features associated with the sensor data may be based variously on detected sounds, motions, images, and the like. The exemplary method further includes determining, in parallel, multiple probable objects based at least in part on the identified features. Various embodiments of the method also include forming hypotheses based at least in part on associating identified features with the multiple probable objects and attributing the formed hypotheses to channels. Sequence of the formed hypotheses are constructed. The exemplary system includes a tracking module configured to provide the channels and constructed sequences for use in various signal processing, such as signal enhancement.
96 Citations
20 Claims
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1. A system for estimating and tracking multiple attributes of multiple objects from multi-sensor data, the system comprising:
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an object detector stored in memory and executed by at least one processor to determine multiple probable objects based at least in part on features associated with sensor data, the sensor data representing data captured by at least one of a plurality of sensors, the determination being made in parallel for the features; a hypothesis generator stored in memory and executed by the at least one processor to form hypotheses based at least in part on associating the features with the multiple probable objects; a grouping module stored in memory and executed by the at least one processor to attribute the formed hypotheses to channels; and a tracking module stored in memory and executed by the at least one processor to construct sequences of the formed hypotheses;
the tracking module being configured to provide the channels and constructed sequences for use in signal processing. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
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19. A method for estimating and tracking multiple attributes of multiple objects from multi-sensor data, the method comprising:
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determining multiple probable objects based at least in part on features associated with sensor data, the sensor data representing data captured by at least one of a plurality of sensors, the determining being performed in parallel for the features; forming hypotheses based at least in part on associating the features with the multiple probable objects; attributing the formed hypotheses to channels; and constructing sequences of the formed hypotheses;
the channels and constructed sequences being configured for use in signal processing.
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20. A non-transitory computer-readable storage medium having embodied thereon instructions, which when executed by one or more processors, perform steps of a method, the method comprising:
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determining multiple probable objects based at least in part on features associated with sensor data, the sensor data representing data captured by at least one of a plurality of sensors, the determination being made in parallel for the features; forming hypotheses based at least in part on associating the features with the multiple probable objects; attributing the formed hypotheses to channels; and constructing sequences of the formed hypotheses, the channels and constructed sequences being configured for use in signal processing.
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Specification