Vergence Control of Binocular Stereoscopic Camera Using Disparity Information

In a dual lens stereoscopic camera, a convergence point determines the stereopsis effects of a video. When a user zooms an object, a convergence point is fixed since it is not coupled with a zoom function. Due to the fixed convergence point, it is possible for a zoom to cause the excessive binocular disparity resulting in visual discomfort. In this paper, to solve this problem, we build the relational model including all phenomena possible to arise and propose the adjustment methods of a convergence point by the positions of a focus, an object and a convergence point. We also evaluate the experiments measuring a binocular disparity and the subjective test to investigate the visual comfort. The results show that one of the proposed methods produced more comfortable 3D images to viewers than the others.

Section: Related Workmentioning

confidence: 99%

“…References [7][8] proposed the methods to adjust the depth of the 3D images. Reference [7] suggested a stereo auto convergence algorithm to improve the 3D viewing comfort.…”

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Convergence Point Adjustment Improving Visual Discomfort for a Zoom on a Stereoscopic Camera

Kim²,

Kim

2016

“…In the 2D image analysis, the existence of the object evidence inside 452 the dangerous region does not necessarily mean that the object has really fallen down to the railroad tracks since 3D coordinates cannot be retrieved from a 2D image. It is well known that 3D depth information can be computed using stereo vision [16][17][18].A stereo camera was adopted in Ref. 19 to verify that a passenger has fallen.…”

Section: Introductionmentioning

confidence: 99%

3D Vision-based Security Monitoring for Railroad Stations

Park

Lee

2010

Increasing demands on the safety of public train services have led to the development of various types of security monitoring systems. Most of the surveillance systems are focused on the estimation of crowd level in the platform, thereby yielding too many false alarms. In this paper, we present a novel security monitoring system to detect critically dangerous situations such as when a passenger falls from the station platform, or when a passenger walks on the rail tracks. The method is composed of two stages of detecting dangerous situations. Objects falling over to the dangerous zone are detected by motion tracking. 3D depth information retrieved by the stereo vision is used to confirm fallen events. Experimental results show that virtually no error of either false positive or false negative is found while providing highly reliable detection performance. Since stereo matching is performed on a local image only when potentially dangerous situations are found; real-time operation is feasible without using dedicated hardware.

“…A similar technique is explained by Kato [20], who focuses on retrieving camera location using fiducially markers, which are located in the 3D environment as squares of known size with high contrast patterns in the centre. K. C. Kwon [21] proposes a binocular stereoscopic camera vergence control method using disparity information by image processing and estimates the quantity of vergence control.…”

mentioning

confidence: 99%

Precision Evaluation of Three-dimensional Feature Points Measurement by Binocular Vision

Xu¹,

Li²,

Su³

et al. 2011

Binocular-pair images obtained from two cameras can be used to calculate the three-dimensional (3D) world coordinate of a feature point. However, to apply this method, measurement accuracy of binocular vision depends on some structure factors. This paper presents an experimental study of measurement distance, baseline distance, and baseline direction. Their effects on camera reconstruction accuracy are investigated. The testing set for the binocular model consists of a series of feature points in stereo-pair images and corresponding 3D world coordinates. This paper discusses a method to increase the baseline distance of two cameras for enhancing the accuracy of a binocular vision system. Moreover, there is an inflexion point of the value and distribution of measurement errors when the baseline distance is increased. The accuracy benefit from increasing the baseline distance is not obvious, since the baseline distance exceeds 1000 mm in this experiment. Furthermore, it is observed that the direction errors deduced from the set-up are lower when the main measurement direction is similar to the baseline direction.