Stereovision, Trinagulation, Feature Correspondance, Disparity Map
In the modern industrial automation production process, computer vision is becoming one of the key technologies to improve production efficiency and inspect product quality, such as automatic detection of machine parts, intelligent robot control, automatic monitoring of production lines, etc.
In the fields of defense and aerospace, computer vision also has more important significance, such as automatic tracking and recognition of moving targets, autonomous car navigation and visual control of space robots.
The purpose of computer vision research is to make computers have the ability to recognize three-dimensional environmental information through two-dimensional image information. This ability not only enables the machine to perceive the geometric information of objects in the three-dimensional environment (such as shape, position, posture movement, etc.), but also to further describe, store, recognize and understand them, computer vision has developed a set of independent calculation theories and algorithms.
In this acticle we introduce the topic of stereo vision which is the application of mutiple camera views to get information about the depth of the view. Using stereo vision one can derive the world location of a point from its images in different camera views.
Stereo Vision
Binocular Stereo Vision is an important form of machine vision. It is based on the principle of parallax and uses imaging equipment to obtain two images of the measured object from different positions.
Dense Stereo Vision takes two input images, left and right, which are shifted and matched to generate the depth of each pixel. Source
Combining the images obtained by the two positions and observing the difference between them, so that we can obtain a clear sense of depth, establish the correspondence between features, and map the same physical point in the same space to the image points in different images. This difference is called a Disparity Map.
#depth-estimation #image-processing #computer-vision #machine-learning #3d-computer-graphics #deep learning