A Fast and Reliable Image Mosaicing Technique with Application to Wide Area Motion Detection

Image mosaicing is stirring up a lot of interests in the research community for both its scientific significance and potential spinoff in real world applications. Being able to perform automatic image alignment in a common tonal and spatial reference can trigger a wide range of higher level image processing tasks such as panoramic image construction, scene depth computation, resolution enhancement, motion detection and tracking using non stationary camera. In this work we propose a fully automated real time on-line mosaicing algorithm able to build high quality seam-free panoramic images. Moreover, the whole approach does not exploit any a priori information regarding scene geometry, acquisition device properties or feedback signals, thus resulting in a fully image based solution. Extensive experiments have been accomplished to assess the quality of the attained mosaics by using them as the background to perform motion detection and tracking with a Pan Tilt Zoom camera.

[1]  M. Pollefeys,et al.  Radiometric Self-Alignment of Image Sequences ( CVPR ’ 04 ) , 2004 .

[2]  Richard Szeliski,et al.  Seamless Image Stitching of Scenes with Large Motions and Exposure Differences , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[3]  Shree K. Nayar,et al.  Determining the Camera Response from Images: What Is Knowable? , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  George Wolberg,et al.  Image registration using log-polar mappings for recovery of large-scale similarity and projective transformations , 2005, IEEE Transactions on Image Processing.

[5]  David Capel,et al.  Image Mosaicing and Super-resolution , 2004, Distinguished Dissertations.

[6]  Allen R. Hanson,et al.  Fast generation of dynamic and multi-resolution 360/spl deg/ panorama from video sequences , 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

[7]  Edward H. Adelson,et al.  A multiresolution spline with application to image mosaics , 1983, TOGS.

[8]  Alessandro Bevilacqua,et al.  Joint Spatial and Tonal Mosaic Alignment for Motion Detection with PTZ Camera , 2006, ICIAR.

[9]  Mohamed S. Kamel,et al.  Image Analysis and Recognition , 2014, Lecture Notes in Computer Science.

[10]  Jan Flusser,et al.  Image registration methods: a survey , 2003, Image Vis. Comput..

[11]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[12]  Carlo Tomasi,et al.  Good features to track , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[13]  Neil A. Dodgson,et al.  Color histogram specification by histogram warping , 2005, IS&T/SPIE Electronic Imaging.

[14]  Luigi di Stefano,et al.  An efficient change detection algorithm based on a statistical nonparametric camera noise model , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[15]  Frank M. Candocia.  Jointly registering images in domain and range by piecewise linear comparametric analysis , 2003, IEEE Trans. Image Process..

[16]  Matthew A. Brown,et al.  Recognising panoramas , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[17]  Ioannis Patras,et al.  Online globally consistent mosaicing using an efficient representation , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[18]  David Capel.  Image Mosaicing and Super-Resolution (Cphc/Bcs Distinguished Dissertations.) , 2004 .

[19]  Luigi di Stefano,et al.  An effective real-time mosaicing algorithm apt to detect motion through background subtraction using a PTZ camera , 2005, IEEE Conference on Advanced Video and Signal Based Surveillance, 2005..

[20]  Harpreet S. Sawhney,et al.  True Multi-Image Alignment and Its Application to Mosaicing and Lens Distortion Correction , 1999, IEEE Trans. Pattern Anal. Mach. Intell..