http://ieeexplore.ieee.org TOC Alert for Publication# 83 2012 February 10 21 2 C1 C4 191 21 2 C2 C2 39 21 2 441 450 1361 21 2 451 458 5200 21 2 459 468 2014 k -nearest neighbor selection of the input LR image patches is conducted in the unified feature subspace to estimate the reconstruction weights. To handle a large number of samples, joint learning locally exploits a coupled constraint by linking the LR-HR counterparts together with the K-nearest grouping patch pairs. In order to refine further the initial SR estimate, we impose a global reconstruction constraint on the SR outcome based on the maximum a posteriori framework. Preliminary experiments suggest that the proposed algorithm outperforms NE-related baselines.]]> 21 2 469 480 1319 21 2 481 493 1480 21 2 494 504 2050 21 2 505 516 1516 21 2 517 526 566 21 2 527 536 3854 21 2 537 549 1568 21 2 550 561 5428 21 2 562 572 1220 21 2 573 587 5070 21 2 588 600 2709 21 2 601 614 3528 21 2 615 625 7578 21 2 626 637 1838 l₂ - and l₁ -based methods. We show that l₂-based techniques can directly estimate the difference image from the measurements without first reconstructing the object scene. This direct estimation exploits the spatial and temporal correlations between the object scene at two consecutive time instants. We further develop a method to estimate a generalized difference image from multiple measurements and use it to estimate the sequence of difference images. For l₁-based estimation, we consider modified forms of the total-variation method and basis pursuit denoising. We also look at a third method that directly exploits the sparsity of the difference image. We present results to show the efficacy of these techniques and discuss the advantages of each.]]> 21 2 638 652 1971 21 2 653 661 780 21 2 662 673 1202 21 2 674 687 2271 21 2 688 696 3172 ° , the proposed framework outperforms algorithms based on the uniform light-source assumption (with error-reduction up to approximately 30%). Otherwise, when the chromatic difference is less than 1^° and the scene can be considered to contain one (approximately) uniform light source, the performance of the proposed method framework is similar to global color constancy methods.]]> 21 2 697 707 1342 21 2 708 717 706 21 2 718 732 5881 O(n²logn) operations for images of size n ×n. In this paper, we demonstrate the applicability of the inverse DRT for the reconstruction of a 2-D object from its continuous projections. The DRT and its inverse are shown to model accurately the continuum as the number of samples increases. Numerical results for the reconstruction from parallel projections are presented. We also show that the inverse DRT can be used for reconstruction from fan-beam projections with equispaced detectors.]]> 21 2 733 741 3226 21 2 742 753 1329 21 2 754 767 1554 21 2 768 777 716 21 2 778 788 1165 21 2 789 801 1212 ° by overcoming the problems introduced by extreme head poses. Moreover, the accuracy of the head pose tracker is improved by 12% to 24%. Finally, the experimentation on the proposed combined gaze estimation system shows that it is accurate (with a mean error between 2^° and 5^°) and that it can be used in cases where classic approaches would fail without imposing restraints on the position of the head.]]> 21 2 802 815 1703 21 2 816 827 1167 21 2 828 843 2135 21 2 844 858 1440 21 2 859 872 1126 21 2 873 882 1413 21 2 883 888 902 21 2 889 898 1257 21 2 898 903 457 21 2 904 904 21 21 2 905 906 46 21 2 907 907 225 21 2 908 908 205 21 2 C3 C3 34