Moving Object's Detect in a Monocular Moving Camera

Recently, there has been increasing interest in using mobile robots within spaces where humans reside, and safe navigation by effective sensing becomes an important issue. In this paper, we describe a method to detect moving objects that exist in front of an autonomously navigating robot by analyzing images of a monocular color camera mounted on the robot. In particular, detecting humans who walk in a direction opposite to the robot's motion is studied because this increases the danger of collision between the pedestrians and the robot. Although moving object detection and obstacle avoidance have been actively studied in the fields of computer vision and intelligent robotics, respectively, analyzing the images of a moving camera is still challenging. One method presented in this paper is based on comparing the current image and a past image in order to find moving objects in the scene. Assuming that the speed of the robot is known, a correspondence between a certain part of the current image and a matching part of a past image is established. Approaching objects can then be detected for a case in which the degree of mismatch between the two corresponding image parts is high. Another method we employ is the detection of human faces. Since a human face has unique features in color and shape, we can search faces in images in order to detect approaching humans. We propose a fast and simple masking method for face detection in a small search region specified from appearance-based foot detection. These two proposed methods were combined to effectively find approaching humans in our experiments. We could get promising test results.