Depth perception is a system’s ability to estimate how far away objects are. In stereo vision, two cameras capture a scene from slightly different positions. Software matches features between the images and uses their positional difference, called disparity, to estimate distance. Accuracy depends on factors such as camera calibration, image quality, lighting, and reliable feature matching.
In cyber security, depth perception matters when computer vision informs physical or automated decisions. A robot or inspection system may rely on estimated distances to navigate or identify objects, so incorrect measurements can lead to unsafe behavior or unreliable results. Defenders and developers should validate sensor outputs, test under varied conditions, and treat depth estimates as measurements with uncertainty-not unquestionable truth.