Human Tracking of Single Laser Range Finder Using Features Extracted by Deep Learning | IEEE Conference Publication | IEEE Xplore

Human Tracking of Single Laser Range Finder Using Features Extracted by Deep Learning

Publisher: IEEE

Abstract:

Human recognition using single laser range finder (LRF) is utilized for the task of following a target person such as a cargo transport robot. In these recognition method...View more

Abstract:

Human recognition using single laser range finder (LRF) is utilized for the task of following a target person such as a cargo transport robot. In these recognition methods, the approach is applied in which human-crafted features is inputted to the one-class classification model to identify whether it is a human or not. In this paper, we propose a method that introduce features extracted by deep learning. In this method, we create an encoder that can extract features from input data using PointNet-based autoencoder. In its experiment, the features extracted by encoder is compared with the human-crafted features, and these extraction process length of time is measured.
Date of Conference: 04-06 November 2019
Date Added to IEEE Xplore: 24 February 2020
ISBN Information:
Publisher: IEEE
Conference Location: Kathmandu, Nepal

References

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