Ego-Motion Estimation for Efficient City Modeling by Using Epipolar Plane Range Image Analysis

This paper proposes a novel notion of Epipolar Plane Range Image (EPRI). A line-scanning laser range sensor is mounted on the side of our data acquisition vehicle, repeating drawing horizontal scanning lines. Laminating the line range data along time axis, we can follow temporal continuity of horizontal cross section of the geometry seen from the scanner, hence can estimate the motion of the vehicle. Applying these information to another vertical-line-scanning range data we can align the position of the scanning lines, and can efficiently get correct 3D geometric model of the real urban space, even if the vehicle travels in arbitrary speed without any external devices as GPS. INTRODUCTION Construction of a 3-D geometric city model in a virtual world has become a highly interested research topic among a lot of research fields, such as computer vision/graphics, virtual/mixed reality, sensing, architectonics, etc. Urban environment models are used in various applications, including urban planning, disaster prevention, intelligent transport systems, or propagation simulation of radio waves for the cell phone industry. Such extensive environments as urban scene are not able to be scanned by one sensing device at once, because current, commercially available sensing devices can not cover whole of the enverionment without occlusion and with enough resolution at the same time. General solutions for this problem are as follows: “Stop-and-go” scanning “Continuous” scanning “Stop-and-go” scanning is a method to scan objects from fixed point, and move to another point, scan, repeatedly. Since the scanning is done from fixed points, the acquired data becomes relatively dense and accurate. Meanwhile, it takes long time to apply to extensive environment as urban scenes. “Continuous” scanning is a powerful and efficient method to solve the demerit of “Stop-and-go” scanning. It is a method to scan objects with the sensor continuously moving. The sensor is mounted on some kind of movable body, such as vehicle, helicopter, airplane, etc. This method is suited to scan extensive areas, however, the ego-motion of the scanner, i.e. the velocity/position of the vehicle, helicopter, airplane, etc. must be known by some techniques. The most popular solution for this problem is to mount other external devices as GPS or INS on the scanning vehicle([3]). It is a highly simple and convenient technique, and the position or the velocity can be acquired in an easy way. However, the accuracy of the positioning result muchly depends on the condition, especially on the reception situation of the radiowave signal. Though the situation improved since the scramble noize addition to the GPS signal has been abolished, the accuracy is still not enough in the ground level of urban area, because of the occulusion by buildings or raised expressway road. Another approach is proposed by C.Frueh et.al([4]). They mount a line-scanning laser range finder on the data acquisition vehicle, and let it sweep horizontal scanning lines. By matching each result of scanning frame pairwise, the ego-motion of the data acquisition vehicle can be acquired. They constructed 3-D virtual textured model of the urban space by using this technique([5, 6]). We also agree to the spirit of this approach: external devices as GPS are suited to acquire initial position of the scanner, and detail position is acquired by computational process of acquired geometric data. In concrete terms, the positional information is acquired by horizontal-scanning laser range finder on our data acquisition vehicle in a similar way. But one of the characteristic aspect of our approach in contrast to [4] is the consideration of temporal continuity of each scanning frames. We propose a novel notion of Epipolar Plane Range Image(EPRI) from Epipolar Plane Image(EPI), which is a classical analysis method of moving image. EPRI simultaneously represents spatial feature and temporal continuity. We estimate the ego-motion of our data aquisition vehicle by analyzing the EPRI. This paper is composed of five sections. After the introduction is brought up in this section, the notion of epipolar plane range image which we propose is described first. Secondly, the EPRI technique is adopted to estimate the ego-motion of the data acquisition vehicle, with outdoor experiment in practice. Finally, the paper is concluded. EPIPOLAR PLANE RANGE IMAGE In this section, we introduce a novel notion of Epipolar Plane Range Image(EPRI), which is a coined term in this paper. EPRI is a spatio-temporal range image representing both spatial feature and temporal continuity simultaneously. The notion of EPRI is derived from Epipolar Plane Image (EPI). Here we firstly explain the EPI analysis, and secondly the EPRI. EPIPOLAR PLANE IMAGE Epipolar Plane Image(EPI) analysis is one of the well-known methods to analyze moving image, especially in the field of computer vision. The notion of EPI was firstly proposed in [1, 2], and various kinds of applied reserches has been proposed. EPI can be created by moving a line camera ( pixel) horizontally, and stacking each image frame vertically(Fig.1). Figure 1: Epipolar Plane Image (EPI) As shown in Fig.1, when the camera moves horizontally, pixels in each frame of the EPI which represent same point in real world compose a continuous edge. The edge image includes various slopes. These variety of the slopes are derived by the parallax, which is the result of the difference of horizontal position of the camera. Fig.2 represents the change of parallax when the camera moves from C1 to C2. From this figure, the depth (horizontal distance from the camera) and the parallax are related with