@article{3152, abstract = {The basic concepts of the molecular machinery that mediates cell migration have been gleaned from cell culture systems. However, the three-dimensional environment within an organism presents migrating cells with a much greater challenge. They must move between and among other cells while interpreting multiple attractive and repulsive cues to choose their proper path. They must coordinate their cell adhesion with their surroundings and know when to start and stop moving. New insights into the control of these remaining mysteries have emerged from genetic dissection and live imaging of germ cell migration in Drosophila, zebrafish, and mouse embryos. In this review, we first describe germ cell migration in cellular and mechanistic detail in these different model systems. We then compare these systems to highlight the emerging principles. Finally, we contrast the migration of germ cells with that of immune and cancer cells to outline the conserved and different mechanisms.}, author = {Kunwar, Prabhat S and Daria Siekhaus and Lehmann, Ruth}, journal = {Annual Review of Cell and Developmental Biology}, pages = {237 -- 265}, publisher = {Annual Reviews}, title = {{In vivo migration A germ cell perspective}}, doi = {10.1146/annurev.cellbio.22.010305.103337}, volume = {22}, year = {2006}, } @inproceedings{3189, abstract = {This paper presents an algorithm capable of real-time separation of foreground from background in monocular video sequences. Automatic segmentation of layers from colour/contrast or from motion alone is known to be error-prone. Here motion, colour and contrast cues are probabilistically fused together with spatial and temporal priors to infer layers accurately and efficiently. Central to our algorithm is the fact that pixel velocities are not needed, thus removing the need for optical flow estimation, with its tendency to error and computational expense. Instead, an efficient motion vs non-motion classifier is trained to operate directly and jointly on intensity-change and contrast. Its output is then fused with colour information. The prior on segmentation is represented by a second order, temporal, Hidden Markov Model, together with a spatial MRF favouring coherence except where contrast is high. Finally, accurate layer segmentation and explicit occlusion detection are efficiently achieved by binary graph cut. The segmentation accuracy of the proposed algorithm is quantitatively evaluated with respect to existing ground-truth data and found to be comparable to the accuracy of a state of the art stereo segmentation algorithm. Fore-ground/background segmentation is demonstrated in the application of live background substitution and shown to generate convincingly good quality composite video.}, author = {Criminisi, Antonio and Cross, Geoffrey and Blake, Andrew and Vladimir Kolmogorov}, pages = {53 -- 60}, publisher = {IEEE}, title = {{Bilayer segmentation of live video}}, doi = {10.1109/CVPR.2006.69}, volume = {1}, year = {2006}, } @article{3190, abstract = {Algorithms for discrete energy minimization are of fundamental importance in computer vision. In this paper, we focus on the recent technique proposed by Wainwright et al. (Nov. 2005)- tree-reweighted max-product message passing (TRW). It was inspired by the problem of maximizing a lower bound on the energy. However, the algorithm is not guaranteed to increase this bound - it may actually go down. In addition, TRW does not always converge. We develop a modification of this algorithm which we call sequential tree-reweighted message passing. Its main property is that the bound is guaranteed not to decrease. We also give a weak tree agreement condition which characterizes local maxima of the bound with respect to TRW algorithms. We prove that our algorithm has a limit point that achieves weak tree agreement. Finally, we show that, our algorithm requires half as much memory as traditional message passing approaches. Experimental results demonstrate that on certain synthetic and real problems, our algorithm outperforms both the ordinary belief propagation and tree-reweighted algorithm in (M. J. Wainwright, et al., Nov. 2005). In addition, on stereo problems with Potts interactions, we obtain a lower energy than graph cuts.}, author = {Vladimir Kolmogorov}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, number = {10}, pages = {1568 -- 1583}, publisher = {IEEE}, title = {{Convergent tree reweighted message passing for energy minimization}}, doi = {10.1109/TPAMI.2006.200}, volume = {28}, year = {2006}, } @inproceedings{3188, abstract = {We introduce the term cosegmentation which denotes the task of segmenting simultaneously the common parts of an image pair. A generative model for cosegmentation is presented. Inference in the model leads to minimizing an energy with an MRF term encoding spatial coherency and a global constraint which attempts to match the appearance histograms of the common parts. This energy has not been proposed previously and its optimization is challenging and NP-hard. For this problem a novel optimization scheme which we call trust region graph cuts is presented. We demonstrate that this framework has the potential to improve a wide range of research: Object driven image retrieval, video tracking and segmentation, and interactive image editing. The power of the framework lies in its generality, the common part can be a rigid/non-rigid object (or scene), observed from different viewpoints or even similar objects of the same class.}, author = {Rother, Carsten and Vladimir Kolmogorov and Minka, Thomas P and Blake, Andrew}, pages = {993 -- 1000}, publisher = {IEEE}, title = {{Cosegmentation of image pairs by histogram matching - Incorporating a global constraint into MRFs}}, doi = {10.1109/CVPR.2006.91}, year = {2006}, } @inproceedings{3214, abstract = {The Feistel-network is a popular structure underlying many block-ciphers where the cipher is constructed from many simpler rounds, each defined by some function which is derived from the secret key. Luby and Rackoff showed that the three-round Feistel-network – each round instantiated with a pseudorandom function secure against adaptive chosen plaintext attacks (CPA) – is a CPA secure pseudorandom permutation, thus giving some confidence in the soundness of using a Feistel-network to design block-ciphers. But the round functions used in actual block-ciphers are – for efficiency reasons – far from being pseudorandom. We investigate the security of the Feistel-network against CPA distinguishers when the only security guarantee we have for the round functions is that they are secure against non-adaptive chosen plaintext attacks (nCPA). We show that in the information-theoretic setting, four rounds with nCPA secure round functions are sufficient (and necessary) to get a CPA secure permutation. Unfortunately, this result does not translate into the more interesting pseudorandom setting. In fact, under the so-called Inverse Decisional Diffie-Hellman assumption the Feistel-network with four rounds, each instantiated with a nCPA secure pseudorandom function, is in general not a CPA secure pseudorandom permutation.}, author = {Maurer, Ueli M and Oswald, Yvonne A and Krzysztof Pietrzak and Sjödin, Johan}, pages = {391 -- 408}, publisher = {Springer}, title = {{Luby Rackoff ciphers from weak round functions }}, doi = {10.1007/11761679_24}, volume = {4004}, year = {2006}, }