The fundamental history of stereo imaging is covered in this overview, as well as how depth knowledge may be extracted from images using this technique. Two-dimensional camera's image does not carry any detailed information. Nevertheless, depth data is necessitated by many applications, such as automatic map-making, robots sensing, and target acquisition. Figure 1 a, b represents the stereo image design (Lo and Chalmers, 2003). There are numerous methods for extracting detailed information, including:
We receive two separate views of the same item from the two cameras, with the usual perspective of a cube depicted in figure 2. As a result, we only notice shifts in the vertical lines, something we may use to measure the depth. This technology is comparable to the human visual system, which has two eyes spaced roughly 60–70 mm apart, resulting in two somewhat distinct views of a tri objects.
Error in Depth Measure
While deploying this system, it is important to take into account the faults that may be made and how they may impact the workflow. We will only be able to identify the picture of P with a specific degree of precision in any image acquisition, which is normally determined by the spatial sampling of the image (Liu et al., 2013). Hence, if we assume a dx inaccuracy in the Dx calculation, we obtain
Therefore, if we define as the ideal distance between the lens and object position P provided by
The depth measurement we will then acquire is v = v0} dv. Since the error in Dx, will cause an error in the depth measure of dv. Using Taylor expansion, we can then determine that dv is terms of dx, to be
So substituting for Dx0, we get that
This demonstrates that the error in the depth measurement increases with the square of the distance from the camera for a fixed S and dx. Therefore, a large S and thus a large camera separation are required to obtain strong depth resolution, but we should also anticipate low depth resolution for distant objects (Fröhlich et al., 1995).
Typical System: Consider a typical, real-world example of stereo imaging utilising two CCD cameras with standard video quality. The size of the one CCD sensor, which is normally around 20 mm for a respectable camera, determines the error dx for a CCD camera. The other parameters are typical. 20 m Sensor Size (dx) 25mm focal length (typical) separation If we plug in the figures for various approximations of distances, we arrive at 100mm (Boher et al., 2014). Figure 3 explains the Stereo photography from a moving aircraft.
v0 » 1m Þ dv » 8mm
v0 » 10m Þ dv » 800mm
Figure 3. Stereo photography from a moving aircraft
For entities that are very close to us, up to a length of approximately 100c m, we are capable of attaining a depth resolution that is better than 1%, but as the distance goes to 1000 cm, the error extends to over 10%, which is rather inadequate. Stereo vision works well up to around 1000 cm, much like the human visual system; after that, we utilise size and perspective to gauge distance.