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Method and system for distributed multiple target tracking

A tracking system and distributed technology, applied in the field of multi-target tracking, can solve problems such as increasing complexity

Inactive Publication Date: 2008-11-05
通用电气保安公司
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  • Summary
  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

However, due to the centralized nature of the joint state representation, the complexity of these methods increases exponentially with the number of tracked objects

Method used

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  • Method and system for distributed multiple target tracking
  • Method and system for distributed multiple target tracking
  • Method and system for distributed multiple target tracking

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Embodiment Construction

[0018] Various embodiments of the present invention provide a method and system for distributed tracking of multiple targets. The Variational Expectation Maximization (EM) algorithm is used to calculate the motion state variables and data association variables of multiple trackers. The plurality of trackers track their corresponding targets based on the calculated motion state variables and data association variables.

[0019] Figure 1 illustrates an environment 100 in which embodiments of the present invention may be implemented. Environment 100 includes three objects 102a , 102b , and 102c , and display 104 . The display 104 displays on its screen the target being continuously tracked. Display 104 may be employed in congested areas, such as airports, so that the movement of people in the airport can be tracked and unusual activity can be detected. Video images displayed on display 104 may be monitored by a human operator and / or subsequently reviewed by a human operator. ...

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Abstract

A method and system (200) for distributed tracking of multiple targets (102) is disclosed. Multiple targets (102) to be tracked by a plurality of trackers (502) are detected in a frame (204). The motion state variable of each of the plurality of trackers (502) is calculated in the E-step of a variational Expectation-Maximization algorithm. Further, the data association variable (302) of each of the plurality of trackers (502) is calculated in the M-step of the algorithm. Depending on the motion state variable and the data association variable (302), the multiple targets (102) are tracked.

Description

[0001] Cross References to Related Applications [0002] This application claims priority to US Provisional Application No. 60 / 912945, filed April 20, 2007, which is incorporated herein by reference in its entirety. technical field [0003] The present invention relates generally to multiple target tracking, and more particularly to methods and systems for tracking multiple targets in a surveillance system. Background technique [0004] Tracking multiple objects is critical in many applications such as video observation, traffic monitoring, human activity analysis, motion video analysis, etc. In addition to tracking the position of the target, other characteristics of the target such as its speed, size, etc. can also be tracked. Analysis of the target's trajectory can predict the target's future path so that appropriate actions can be taken. For example, it is vital to track the movement of people in a crowded area such as an airport so that unusual activity can be detecte...

Claims

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Application Information

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IPC IPC(8): G06T7/20
Inventor 喻颋P·H·土A·G·A·佩雷拉J·里特谢尔N·O·克拉恩斯特弗刘小明
Owner 通用电气保安公司
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