## 3 Materials and Methods
### Identifying PVI Location
#### 3.2.1 Comparing QR code with Aruco markers  
To select which tag is the best, the authors have compared them based on certain criteria [5]. The first criterion is the cost of applying the technology to any solution. It is shown that CV tag  
Figure 4: A graph of the fourth floor’s corridor at the same faculty. techniques can be used without any cost except for printing the QR codes or AR markers and putting them in the correct place. When using a barcode, there is no need to print them, as they are already placed on each product. Tag-based techniques can be used at a low cost, as shops only need the RFID or NFC tags to be installed in the correct places. If CV techniques are used, high-quality equipment, such as cameras, are required for satisfactory results. The second criterion is the equipment needed to detect and identify products or places. For CV tag-based solutions, PVI only need their smartphone cameras to detect and identify items. For non-CV tag-based techniques, some solutions only need a smartphone's camera, while others need high-quality cameras to capture high resolution images and machines with powerful processors for computation. In tag-based techniques, PVI need RFID readers or smartphones supporting NFC technology. The third criterion is the number of items to be scanned simultaneously. Only RFID readers, AR markers, and CV techniques can scan multiple items at the same time, which is useful in some situations, such as if PVI want to identify and count the items in their shopping cart. The fourth criterion is whether the PVI must be in the line of sight with the identified products or not. For tag-based solutions, PVI do not have to be in the line of sight of items, and the PVI can identify them in any direction. In tag-based solutions, there is no need for RFID tags and NFC tags to be in the line of sight, while CV solutions depend on some other parameters, such as the tag size in QR codes or barcodes, and the marker or camera parameters for CV techniques. The fifth criterion is the storage capacity of each solution. Only some tags, such as RFID, NFC, and QR codes, have a storage capacity, while others, such as AR markers and barcodes, do not have any storage capacity. The last criterion is the detection range, in tag-based solutions, tags must be within 3 m for RFID tags and within 10 cm for NFC tags. In CV tag-based solutions, tags can be detected from a distance which depends on tag size and image resolution. Based on this evaluation, the authors found that QR codes and markers were the most suitable markers to select. So, the authors have compared QR codes with markers to select which give more accuracy and put together the following hypotheses:  
**H1:**: _Aruco markers are better than QR codes._
**H2:**: _Aruco markers can be detected from long distances._  
The authors have developed two applications to identify the location of PVI with the architecture shown in Figure 5.  
An important task after the detection and identification of markers is to obtain the camera's position from them. For the position estimation, the authors need to know the parameters of the camera which came from the calibration. These parameters are the camera matrix and the distortion coefficients. The camera has some parameters such as extrinsic, intrinsic, and distortion coefficients. To estimate these parameters, it is important to have 3D world points of a real scene and the corresponding 2D image points which are called camera calibration. Camera calibration estimates the parameters of the lens and sensor of an image which makes it important for AR applications. This can be done using multiple images of a pattern such as a checkerboard, square grid, circle hexagonal grid or circle regular grid. So, before using the two applications, the authors made camera calibration to obtain the camera position from markers. These applications work the following way: At first, the application opens the camera to get a live stream of images.