Shape from Depth Discontinuities

Author(s):  
Gabriel Taubin ◽  
Daniel Crispell ◽  
Douglas Lanman ◽  
Peter Sibley ◽  
Yong Zhao
Perception ◽  
1996 ◽  
Vol 25 (1_suppl) ◽  
pp. 90-90
Author(s):  
M J M Lankheet ◽  
M Palmen

We previously described the spatiotemporal requirements for binocular correlation in stereopsis using sinusoidal gratings-in-depth (Lankheet and Lennie, 1996 Vision Research36 527 – 538). The use of smooth sinusoidal surfaces emphasised the effects of spatial and temporal integration. Binocular correlation, however, depends not only on integration, but also on segregation at depth discontinuities. In the present experiments we therefore investigated segregation-in-depth, using random dot stereograms that depicted two transparent frontoparallel planes positioned symmetrically on either side of a binocular fixation point. Sensitivity for segregating the two planes was established by adding Gaussian distributed disparity noise to the disparities specifying the planes, and finding the noise amplitude that rendered transparency just detectable. The stimuli consisted of dynamic random-dot displays (dot lifetime 4 frames, at a frame rate of 67 Hz), generated in real time by a Macintosh computer, displayed on a television monitor, and viewed through a stereoscope. We used a method of constant stimuli and a 2AFC procedure. Two transparent planes were presented in one interval, and a single plane, with Gaussian distributed disparity values spanning the same range, was presented in the other. Segregation of stationary patterns was optimal for disparity differences of about ±9 min arc. Differences smaller than ±3 min arc and larger than about ±18 min arc could not be resolved. Motion contrast between the two patterns greatly facilitated segregation in depth. The facilitating effect increased with the difference in motion directions. The optimal speed varied with the difference in disparity.


Robotica ◽  
1997 ◽  
Vol 15 (2) ◽  
pp. 225-231 ◽  
Author(s):  
Christian Barat ◽  
Jean Triboulet ◽  
Youcef Chekhar ◽  
Etienne Colle

A laser range finder mounted on a site and azimuth turret is used as a 3D range camera. It forms, associated with a video camera, an original stereovision system. The internal structure of both images are the same but the resolution of 3D image stays low. By ignoring the acquiring speed of measures, spatial resolution is limited by the accuracy of deviation device and the laser footprint. The fact that the impact of the beam is not a point introduces spatial integration.To correct the average at depth discontinuities due to the beam footprint, a neural-network-based solution is reported.The use of such a multisensor system requires its calibration. As camera calibration is a well-known problem, the paper focuses on models and calibration methods of the range finder. Experimental results illustrate the quality of the calibration step in terms of accuracy and stability.The footprint correction is evaluated for both 1D and 2D range finder scannings.


Geology ◽  
2003 ◽  
Vol 31 (5) ◽  
pp. 399 ◽  
Author(s):  
Christopher Small ◽  
Leonid V. Danyushevsky

2013 ◽  
Vol 288 ◽  
pp. 27-30 ◽  
Author(s):  
Yong Xu ◽  
Shuhai Jia ◽  
Xing Luo ◽  
Jia Yang ◽  
Ye Zhang

Author(s):  
WEI WANG ◽  
CAIMING ZHANG ◽  
SHUOZHEN WANG ◽  
XUEMEI LI

There has been a significant improvement in stereo matching with the introduction of adaptive support weights. Existing local methods mainly focus on the computation of support weight which is critical in cost aggregation and usually get excellent results. However, the negative effects of occluded regions are often ignored, which results in the problem of foreground fattening and blurred depth borders. This paper proposes a novel support aggregation strategy by utilizing the occlusion information obtained from left-right consistency check. The weights of invalid points are noticeably reduced at each disparity estimation stage. Experimental results on the Middlebury images show that our method is highly effective in improving the disparities of points around occluded areas and depth discontinuities. According to the Middlebury benchmark, the proposed method achieves the best performance among all the local methods. Moreover, our approach can be easily integrated into nearly all the existing support weights strategies.


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