6533b825fe1ef96bd1282a20

RESEARCH PRODUCT

Scale invariant line matching on the sphere

Dieu Sang LyCédric DemonceauxRalph SeulinYohan Fougerolle

subject

0209 industrial biotechnologySimilarity (geometry)[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processingmobile roboticComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-invariant feature transformTime to contactmobile robotic.02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingMeasure (mathematics)obstacle avoidance020901 industrial engineering & automation[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processingomnidirectional visionDistortion0202 electrical engineering electronic engineering information engineeringPoint (geometry)Computer visionCollision detectioncollision detectionMathematics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingbusiness.industryPerspective (graphical)Computer Science::Computer Vision and Pattern RecognitionLine (geometry)020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing

description

International audience; This paper proposes a novel approach of line matching across images captured by different types of cameras, from perspective to omnidirectional ones. Based on the spherical mapping, this method utilizes spherical SIFT point features to boost line matching and searches line correspondences using an affine invariant measure of similarity. It permits to unify the commonest cameras and to process heterogeneous images with the least distortion of visual information.

yearjournalcountryeditionlanguage
2013-09-01
https://hal.archives-ouvertes.fr/hal-00830884