http://ieeexplore.ieee.org TOC Alert for Publication# 4159597 2012 February 10 6 1 1 12 1504 L_∞-norm. The main advantage of this approach is a theoretical guarantee of global optimality. First, three core problems in multiview geometry in traditional vision are formulated as second-order cone programming feasibility problems. The extension of L_∞-norm approach for multiview geometry from traditional vision to omnidirectional vision is shown by three models, a mirror model, a sphere model and a cylinder model. Finally, the authors assess their potential for future deployment and present directions for future research.]]> 6 1 13 20 346 6 1 21 28 537 6 1 29 39 1505 6 1 40 51 1404 6 1 52 61 841 et al. attempts to reduce the interference of background in target localisation in mean-shift tracking. However, the authors prove that the weights assigned to pixels in the target candidate region by BWH are proportional to those without background information, that is, BWH does not introduce any new information because the mean-shift iteration formula is invariant to the scale transformation of weights. Then a corrected BWH (CBWH) formula is proposed by transforming only the target model but not the target candidate model. The CBWH scheme can effectively reduce background's interference in target localisation. The experimental results show that CBWH can lead to faster convergence and more accurate localisation than the usual target representation in mean-shift tracking. Even if the target is not well initialised, the proposed algorithm can still robustly track the object, which is hard to achieve by the conventional target representation.]]> 6 1 62 69 661 6 1 70 78 572