Stereo sensors

Stereo sensors try to mimic human vision by using two cameras facing the scene with some distance between them (baseline, see Figure 1). The images from these cameras are acquired and then used to perform visual feature (relevant visual information) extraction and matching to obtain a disparity map between the cameras’ views.

The disparity information is inversely proportional to depth and can easily be used to obtain the depth map. This also means that some sensors of this type usually only work in feature-rich environments and encounter problems in featureless environments (e.g. a white wall). However, this type of sensor usually allows for greater depth image resolutions than other cameras.

These feature detection and matching computations are done onboard the camera, meaning they usually require more processing power than other methods. Also, the stereo working distance is limited by the baseline between the cameras as the error increases quadratically with objects’ distance to the sensor. Usual applications entail both indoor and outdoor, feature-rich environments.