TY - CHAP
T1 - Panorama Construction from Multi-view Cameras in Outdoor Scenes
AU - JAIN, Lakhmi
AU - Favorskaya, Margarita
AU - Novikov, Dmitry
PY - 2015
Y1 - 2015
N2 - The applications of panoramic images are wide spread in computer vision including navigation systems, object tracking, virtual environment creation, among others. In this chapter, the problems of multi-view shooting and the models of geometrical distortions are investigated under the panorama construction in the outdoor scenes. Our contribution are the development of procedure for selection of “good” frames from video sequences provided by several cameras, more accurate estimation of projective parameters in top, middle, and bottom regions in the overlapping area during frames stitching, and also the lighting improvement of the result panoramic image by a point-based blending in a stitching area. Most proposed algorithms have high computer cost because of mega-pixel sizes of initial frames. The reduction of frames sizes, the use of CUDA technique, or the hardware implementation will improve these results. The experiments show good visibility results with high stitching accuracy, if the initial frames were selected well
AB - The applications of panoramic images are wide spread in computer vision including navigation systems, object tracking, virtual environment creation, among others. In this chapter, the problems of multi-view shooting and the models of geometrical distortions are investigated under the panorama construction in the outdoor scenes. Our contribution are the development of procedure for selection of “good” frames from video sequences provided by several cameras, more accurate estimation of projective parameters in top, middle, and bottom regions in the overlapping area during frames stitching, and also the lighting improvement of the result panoramic image by a point-based blending in a stitching area. Most proposed algorithms have high computer cost because of mega-pixel sizes of initial frames. The reduction of frames sizes, the use of CUDA technique, or the hardware implementation will improve these results. The experiments show good visibility results with high stitching accuracy, if the initial frames were selected well
KW - Panorama-construction
KW - multi-view-cameras
KW - outdoor-scenes
KW - Panorama construction
KW - Projective transformation
KW - Image selection
KW - Retinex algorithm
KW - Robust detectors
KW - Texture blending
KW - Image stitching
UR - http://www.scopus.com/inward/record.url?scp=84921377183&partnerID=8YFLogxK
UR - http://www.mendeley.com/research/panorama-construction-multiview-cameras-outdoor-scenes
U2 - 10.1007/978-3-319-11430-9_4
DO - 10.1007/978-3-319-11430-9_4
M3 - Chapter
SN - 9783319114293
VL - 75
T3 - Intelligent Systems Reference Library
SP - 71
EP - 108
BT - Computer Vision in Control Systems-2
A2 - Favorskaya, Margarita
A2 - Jain, Lakhmi
PB - Springer
CY - Germany
ER -