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저해상도 2D 라이다의 사람 특성 함수를 이용한 새로운 사람 감지 기법

A Novel Human Detection Scheme using a Human Characteristics Function in a Low Resolution 2D LIDAR

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초록

Human detection technologies are widely used in smart homes and autonomous vehicles. However, in order to detect human, autonomous vehicle researchers have used a high-resolution LIDAR and smart home researchers have applied a camera with a narrow detection range. In this paper, we propose a novel method using a low-cost and low-resolution LIDAR that can detect human fast and precisely without complex learning algorithm and additional devices. In other words, human can be distinguished from objects by using a new human characteristics function which is empirically extracted from the characteristics of a human. In addition, we verified the effectiveness of the proposed algorithm through a number of experiments.

Abstract

Human detection technologies are widely used in smart homes and autonomous vehicles. However, in order to detect human, autonomous vehicle researchers have used a high-resolution LIDAR and smart home researchers have applied a camera with a narrow detection range. In this paper, we propose a novel method using a low-cost and low-resolution LIDAR that can detect human fast and precisely without complex learning algorithm and additional devices. In other words, human can be distinguished from objects by using a new human characteristics function which is empirically extracted from the characteristics of a human. In addition, we verified the effectiveness of the proposed algorithm through a number of experiments.

참고문헌 (15)

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  15. 이무현, "2D 라이다 데이터베이스 기반 장애물 분류 기법", 대한임베디드공학회논문지, 10(3), pp.179~188 (2015), 대한임베디드공학회[DOI]

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