Efficient Depth Estimation Using Sparse Stereo-Vision with Other Perception Techniques

The stereo vision system is one of the popular computer vision techniques. The idea here is to use the parallax error to our advantage. A single scene is recorded from two different viewing angles, and depth is estimated from the measure of parallax error. This technique is more than a century old and has proven useful in many applications. This field has made a lot of researchers and mathematicians to devise novel algorithms for the accurate output of the stereo systems. This system is particularly useful in the field of robotics. It provides them with the 3D understanding of the scene by giving them estimated object depths. This chapter, along with a complete overview of the stereo system, talks about the efficient estimation of the depth of the object. It stresses on the fact that if coupled with other perception techniques, stereo depth estimation can be made a lot more efficient than the current techniques. The idea revolves around the fact that stereo depth estimation is not necessary for all the pixels of the image. This fact opens room for more complex and accurate depth estimation techniques for the fewer regions of interest in the image scene. Further details about this idea are discussed in the subtopics that follow.