caa a22 4500 445295317 CHVBK 20180317142540.0 cr unu---uuuuu 170323e20100301xx s 000 0 eng 10.1007/s11554-009-0127-z doi (NATIONALLICENCE)springer-10.1007/s11554-009-0127-z Aligning windows of live video from an imprecise pan-tilt-zoom camera into a remote panoramic display for remote nature observation [Elektronische Daten] [Dezhen Song, Yiliang Xu, Ni Qin] A pan-tilt-zoom (PTZ) robotic camera can provide a detailed live video of selected areas of interest within a large potential viewing field. The selective coverage is ideal for nature observation applications where power and bandwidth are often limited. To provide the spatial context for human observers, it is desirable to insert the live video into a large spherical panoramic display representing the entire viewing field. Accurate alignment of the video stream within the panoramic display is difficult due to imprecise pan-tilt values and rapid changes in camera configurations. Common image alignment algorithms are computationally expensive for real time applications. We are interested in designing algorithms that fit low power computation platform and hence can be implemented inside the PTZ camera in the future. We present a sampling-based constant-time image alignment algorithm based on spherical projection and projection-invariant selective sampling that accurately registers paired images at 100 frames per second on a simulated embedded platform. The alignment accuracy actually is better than existing methods when high rotational difference is involved. Experiments suggest that the new alignment algorithm is faster than existing algorithms by 1,471.6times when aligning a six-mega-pixel image pair. Springer-Verlag, 2009 Image alignment nationallicence Pan-tilt-zoom camera nationallicence Panorama video nationallicence Motion panorama nationallicence Nature observation nationallicence Song Dezhen Computer Science and Engineering Department, Texas A&M University, 77843, College Station, TX, USA aut Xu Yiliang Computer Science and Engineering Department, Texas A&M University, 77843, College Station, TX, USA aut Qin Ni Computer Science and Engineering Department, Texas A&M University, 77843, College Station, TX, USA aut Journal of Real-Time Image Processing Springer-Verlag 5/1(2010-03-01), 57-70 1861-8200 5:1<57 2010 5 11554 https://doi.org/10.1007/s11554-009-0127-z text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11554-009-0127-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Song Dezhen Computer Science and Engineering Department, Texas A&M University, 77843, College Station, TX, USA aut NATIONALLICENCE 700 1- Xu Yiliang Computer Science and Engineering Department, Texas A&M University, 77843, College Station, TX, USA aut NATIONALLICENCE 700 1- Qin Ni Computer Science and Engineering Department, Texas A&M University, 77843, College Station, TX, USA aut NATIONALLICENCE 773 0- Journal of Real-Time Image Processing Springer-Verlag 5/1(2010-03-01), 57-70 1861-8200 5:1<57 2010 5 11554 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer