Gaussian Mixture Model (GMM) Based Object Detection and Tracking using Dynamic Patch Estimation

Vishnu Anand; Durgakant Pushp; Rishin Raj; Kaushik Das

IROS 2019poster6 citations

Gaussian Mixture Model (GMM) Based Object Detection and Tracking using Dynamic Patch Estimation

Vishnu Anand, Durgakant Pushp, Rishin Raj, Kaushik Das

Abstract

In this paper, we have developed a Gaussian Mixture Model (GMM) based algorithm with dynamic patch estimation for real-time detection and tracking of a known object. This research work detects the object of interest, estimates its 3-D position using Extended Kalman Filter (EKF) and generates the control output to the quad-rotor to track the target. The proposed algorithm is capable of tracking the object with a high Frame Per Second (FPS). Rigorous experiments are carried out to demonstrate the efficacy of the proposed approach in outdoor environment.

BibTeX

@inproceedings{iros2019_gaussianmixturem,
  title = {Gaussian Mixture Model (GMM) Based Object Detection and Tracking using Dynamic Patch Estimation},
  author = {Vishnu Anand and Durgakant Pushp and Rishin Raj and Kaushik Das},
  booktitle = {IROS 2019},
  year = {2019}
}