Some new understanding of a single-lens binocular stereovision system using a biprism (2F filter) is presented. One image captured by this system is divided into two halves and assumed to be one stereo image pair captured by two virtual cameras generated by the biprism. Hence, this system can also be called a virtual stereovision system. Two different approaches to understanding this system are introduced. One approach is based on a camera calibration technique and another is based on a geometrical analysis of ray sketching. Both approaches enable this system to perform depth recovery in a close range like a typical stereovision system. As the approach based on geometrical analysis requires no complex calibration, great implementation and calibration effort can be saved, in contrast with a normal stereovision system. This approach provides a way to build a binocular stereovision system with a simpler implementation but sufficient accuracy. A complete analysis of this system and the related calibration, depth recovery, and experimentation techniques are presented. Experimentation results are presented to prove the effectiveness of both approaches used to understand this system.
Normal stereovision system requires two or more cameras to capture different views of the same scene. One category of technique called single-lens stereovision attracted many researchers interest because of its significant advantages over the normal stereovision setup including compactness, low cost, less system parameters and ease of calibration, etc. In this paper we present some new understanding of a single-lens stereovision system using a biprism (2F filter). Image captured by the real camera with a biprism placed before its lens, is divided into two equal halves. Each half-image is assumed to be captured by one virtual camera. Two related but different approaches of understanding and modeling such a system are introduced: one is based on camera calibration technique and another is based on geometrical analysis. The latter approach provides an interesting way of understanding this system. It does not require complex calibration, and one field point test is sufficient to determine the system once the system is built and pin-hole camera model is used. Thus, great effort on setup and calibration will be saved compared to normal binocular stereovision system. The approach based on geometrical analysis provides a relatively simpler and sufficiently accurate way of building a close range stereovision system.