*Geographic Information Systems in Geospatial Intelligence*

projected onto the screen and compared with the current pattern on the screen [19]. If there are any obstacles in the way, the IR pattern changes shape from which the depth values can be deciphered. The Kinect v2.0 however, uses ToF technique to acquire depth values, where the sensor measures the time it takes for the modulated laser pulses from the IR projector to reach the object and then back to the IR camera [13]. The RGB resolution of the Kinect v2.0 is at 1920 � 1080 pixels, and the IR camera has a resolution of 512 � 424 pixels, with corresponding pixel sizes of 3.1 and 10 μm respectively. The collection of the ð Þ *x; y; z* points results into 3D point

cloud. This implies at the acquisition rate of 30 frames per second (fps), every frame of the Kinect v2.0 outputs 217,088 colored 3D points. The advantage that the Kinect v2.0 has over its predecessor Xtion Pro Live (Kinect v1.0), is that since it uses the principle of the ToF instead of relying on projected IR patterns for computing depth, the interference problem is greatly reduced as the sensor does not have to compute distances between neighboring points on the pattern [13]. The other advantage with the Kinect v2.0 over the Xtion, is that the camera has a built in ambient-light rejection method, which makes it possible to use in an outdoor environment with near infrared sources of interference [16]. **Table 1(a)** presents a summary of the differences between the Microsoft Kinect sensor v1.0 and other low-cost sensors, and **Table 1(b)** presents the fundamental characteristics of the

*On the Use of Low-Cost RGB-D Sensors for Autonomous Pothole Detection with Spatial…*

**3. Low-cost hardware system design and set-up for pavement data**

ing of the hardware platform and peripheral requirements, with interface for Kinect-computer data acquisition, visualization and storage, in both static and dynamic acquisition modes is illustrated in **Figure 2**, and is termed as integrated Mobile Mapping Sensor System (iMMSS). For the implementation of the iMMSS, two main sets of equipment are used: (i) the Kinect v2.0—for RGB, Infrared (IR) and depth data capture, and (ii) a DC-AC power inverter—12 V DC to AC 220 V/ 200 W output. The power inverter is adaptable to the car charger port for powering the Kinect sensor for static and continuous pavement data acquisition modes. The iMMSS data acquisition system hardware-software set-up is as illustrated in the photo in **Figure 2**. The three main criteria in the field experimentation using the iMMSS comprise of: the shooting angle (vertical and oblique), shooting distance from the pavement, and the overall target positioning. **Figure 2** illustrates the hardware layout and software data capture system. The sensing device is housed within a sensor rack mounted onto the exterior of the wagon. To improve the contrast of the Kinect's laser pattern over the road surfaces, from the reflected IR radiation from sunlight an umbrella was used to block the rays from the sun and to

The establishment and design of an optimal low-cost imaging system, compris-

In terms of data acquisition in static and dynamic mode (**Figure 2**), the Kinect sensor captures depth and color images simultaneously at a frame rate of up to 30 fps. The integration of depth and color data results in a colored point cloud that

*iMMSS hardware-software set-up for road pavement data capture, visualization and storage using the Kinect*

Kinect versions 1.0 and 2.0.

create a shadow.

**Figure 2.**

*sensor.*

**149**

**acquisition using Kinect v2.0**

*DOI: http://dx.doi.org/10.5772/intechopen.88877*


**Table 1.**

*Comparative specifications of Kinect v1.0 and Kinect v2.0 and other low-cost sensors.*

*On the Use of Low-Cost RGB-D Sensors for Autonomous Pothole Detection with Spatial… DOI: http://dx.doi.org/10.5772/intechopen.88877*

cloud. This implies at the acquisition rate of 30 frames per second (fps), every frame of the Kinect v2.0 outputs 217,088 colored 3D points. The advantage that the Kinect v2.0 has over its predecessor Xtion Pro Live (Kinect v1.0), is that since it uses the principle of the ToF instead of relying on projected IR patterns for computing depth, the interference problem is greatly reduced as the sensor does not have to compute distances between neighboring points on the pattern [13]. The other advantage with the Kinect v2.0 over the Xtion, is that the camera has a built in ambient-light rejection method, which makes it possible to use in an outdoor environment with near infrared sources of interference [16]. **Table 1(a)** presents a summary of the differences between the Microsoft Kinect sensor v1.0 and other low-cost sensors, and **Table 1(b)** presents the fundamental characteristics of the Kinect versions 1.0 and 2.0.
