Moving Object Detection from Moving Camera Image Sequences Using an Inertial Measurement Unit Sensor

Abstract

This paper describes a new method for the detection of moving objects from moving camera image sequences using an inertial measurement unit (IMU) sensor. Motion detection systems with vision sensors have become a global research subject recently. However, detecting moving objects from a moving camera is a difficult task because of egomotion. In the proposed method, the interesting points are extracted by a Harris detector, and the background and foreground are classified by epipolar geometry. In this procedure, an IMU sensor is used to calculate the initial fundamental matrix. After the feature point classification, a transformation matrix is obtained from matching background feature points. Image registration is then applied to the consecutive images, and a difference map is extracted to find the foreground region. Finally, a minimum bounding box is applied to mark the detected moving object. The proposed method is implemented and tested with numerous real-world driving videos, which show that it outperforms the previous work. Appl. Sci. 2020, 10, 268 3 of 13 Appl. Sci. 2020, 10, x 3 of 12 Appl. Sci. 2020, 10, 268 13 of 13 34. Mirzaei, F.M.; Roumeliotis, S.I. A Kalman filter-based algorithm for IMU-camera calibration: Observability analysis and performance evaluation.

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