Panorama Mosaic Optimization for Mobile Camera Systems

Ha, Seong Jong; Koo, Hyung Il; Lee, Sang Hwa; Cho, Nam Ik; Kim, Soo Kyun

doi:10.1109/tce.2007.4429204

Cited by 59 publications

(33 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…25,26 For instance, in a recently proposed method based on using graph cuts to find the optimal stitching position, 27 the authors claim to produce consistent mosaics of stereoscopic images. Their method is based on minimizing an energy function specifically designed to account for the depth continuity followed by a warping transformation to smooth disparity transitions between mosaics.…”

Section: Blending Regionsmentioning

confidence: 99%

Depth consistency and vertical disparities in stereoscopic panoramas

Gurrieri

Dubois

2014

J. Electron. Imaging

View full text Add to dashboard Cite

Abstract. In recent years, the problem of acquiring omnidirectional stereoscopic imagery of dynamic scenes has gained commercial interest, and consequently, new techniques have been proposed to address this problem. The goal of many of these new panoramic methods is to provide practical solutions for acquiring real-time omnidirectional stereoscopic imagery for human viewing. However, there are problems related to mosaicking partially overlapped stereoscopic snapshots of the scene that need to be addressed. Among these issues are the conditions to provide a consistent depth illusion over the whole scene and the appearance of undesired vertical disparities. We develop an acquisition model capable of describing a variety of omnistereoscopic imaging systems and suitable to study the design constraints of these systems. Based on this acquisition model, we compare different acquisition approaches based on mosaicking partial stereoscopic views of the scene in terms of their depth continuity constraints and the appearance of vertical disparities. This work complements and extends our previous work in omnistereoscopic imaging systems by proposing a mathematical framework to contrast different acquisition strategies to create stereoscopic panoramas using a small number of stereoscopic images. © 2014 SPIE and IS&T

show abstract

Section: Blending Regionsmentioning

confidence: 99%

Depth consistency and vertical disparities in stereoscopic panoramas

Gurrieri

Dubois

2014

J. Electron. Imaging

View full text Add to dashboard Cite

show abstract

“…Linear blending is applied line by line based on the location of the optimal cut. The linear programming algorithm proposed by Ha et al 20 is based on obtaining the locations of minimum intensity gradient between two images to blend. A scoring system enables to find the optimal cut line by line.…”

Section: Mosaic Stitchingmentioning

confidence: 99%

Stereoscopic cameras for the real-time acquisition of panoramic 3D images and videos

Gurrieri

Dubois

2013

SPIE Proceedings

View full text Add to dashboard Cite

There are different panoramic techniques to produce outstanding stereoscopic panoramas of static scenes. However, a camera configuration capable to capture omnidirectional stereoscopic snapshots and videos of dynamic scenes is still a subject of research. In this paper, two multiple-camera configurations capable to produce high-quality stereoscopic panoramas in real-time are presented. Unlike existing methods, the proposed multiple-camera systems acquire all the information necessary to render stereoscopic panoramas at once. The first configuration exploits micro-stereopsis arising from a narrow baseline to produce omni-stereoscopic images. The second panoramic camera uses an extended baseline to produce poly-centric panoramas and to extract additional depth information, e.g., disparity and occlusion maps, which are used to synthesize stereoscopic views in arbitrary viewing directions. The results of emulating both cameras and the pros and cons of each set-up are presented in this paper.

show abstract

“…Brightness changes over the captured images in the same scene with varying viewpoints may create large color artifact when they are merged [21]- [23]. For color constancy of merging image, color difference of overlapped regions must be corrected.…”

Section: Color Compensation and Color Assignmentmentioning

confidence: 99%