지하 주차장 차량 추적을 위한 객체의 이동 방향 추정

Estimation of Moving Direction of Objects for Vehicle Tracking in Underground Parking Lot
  • Nguyen Huu Thang
  • 김재민

초록

One of the highly reliable object tracking methods is to trace objects by associating objects detected by deep learning. The detected object is represented by a rectangular box. The box has information such as location and size. Since the tracker has motion information of the object in addition to the location and size, knowing additional information about the motion of the detected box can increase the reliability of object tracking. In this paper, we present a new method of reliably estimating the moving direction of the detected object in underground parking lot. First, the frame difference image is binarized for detecting motion energy, change due to the object motion. Then, a cumulative binary image is generated that shows how the motion energy changes over time. Next, the moving direction of the detected box is estimated from the accumulated image. We use a new cost function to accurately estimate the direction of movement of the detected box. The proposed method proves its performance through comparative experiments of the existing methods.

키워드

Moving direction estimationDetected bounding boxVehicle trackingAccumulated binary frame difference image
제목
지하 주차장 차량 추적을 위한 객체의 이동 방향 추정
제목 (타언어)
Estimation of Moving Direction of Objects for Vehicle Tracking in Underground Parking Lot
저자
Nguyen Huu Thang김재민
발행일
2021
저널명
멀티미디어학회논문지
24
2
페이지
305 ~ 311