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Tracking moving objects using particle filter and edge observation model

에지 관측 모델과 파티클 필터를 이용한 이동 객체 추적

  • Received : 2015.12.01
  • Accepted : 2016.05.10
  • Published : 2016.06.30

Abstract

In this paper, we propose a method that is tracking an object in real time using particle filter and the observation model with edge. First of all, the proposed method defines the object to be tracked in the initial frame. Then, it generates the edge observation model for the object to be tracked and a set of particles. It calculates the weight by comparing the average of the middle distance in eight-way of particle filter edge model with that in edge observation model, and then updates the weight with the calculated value. After resampling particles using the updated weights, it estimates the current location of the tracked object. Finally, this paper demonstrates the performance of the stable tracking through comparison with the existing method by using a number of experimental data.

본 논문에서는 에지를 사용한 관측 모델과 파티클 필터를 이용하여 실시간으로 객체를 추적하는 방법을 제안한다. 논문에서 제안하는 방법은 먼저, 초기 프레임에서 추적하고자 하는 객체를 지정한다. 지정된 객체에 대해 에지 관측 모델과 N개의 파티클 필터 집합을 생성한다. 에지 관측 모델과 파티클의 8방향 에지 모델의 중간 거리 평균을 비교하여 가중치를 계산하고, 계산된 값으로 가중치를 업데이트한다. 업데이트된 가중치를 이용해 파티클들을 리샘플링한 후, 추적 객체의 상태인 현재 위치를 추정할 수 있다. 마지막으로 본 논문에서 제안하는 방법은 여러 실험 데이터를 이용하여 기존의 방법과의 비교분석을 통해 안정적인 추적에 대한 성능을 입증한다.

Keywords

References

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