170,186 research outputs found
Bilder und Bedeutungen in der Grammatikvermittlung
No full textWithin the field of foreign language teaching research, studies on metaphor have focused on the importance of imagery in the process of language comprehension (Beißner 2002; Bellavia 2007b, 2014; Boers & Lindstromberg 2008; Danesi 1993, 1995, 1998). This work is based on the assumption that grammar pedagogy which is in line with the results of this research in linguistics and psycho-linguistics must include among its objectives the development of schemata and metaphorical associations as stable contents of learner memory to be drawn upon during the comprehension and production of texts. Starting from those assumptions the paper shows means to approach the learning of grammar in a ‘holistic’ way, which emphasize the meaning conveyed by utterances and the imagery employed in those utterances
Convergence analysis of an Inexact Infeasible Interior Point method for Semidefinite Programming
No full textIn this paper we present an extension to SDP of the well known infeasible Interior Point method for linear programming of Kojima,Megiddo and Mizuno (A primal-dual infeasible-interior-point algorithm for Linear Programming, Math. Progr., 1993). The extension developed here allows the use of inexact search directions; i.e., the linear systems defining the search directions can be solved with an accuracy that increases as the solution is approached. A convergence analysis is carried out and the global convergence of the method is prove
Guest editorial: Local image descriptors in computer vision
No full text...This Special Issue includes seven original research papers that cover diverse and significant aspects of local image descriptor research. In particular, the order in which papers appear reflects the main phase they address, in an ideal computational pipeline starting with the localisation of salient points in an image and ending with the incorporation of spatial and temporal features in descriptor construction...
Rethinking the sGLOH descriptor
No full textsGLOH (shifting GLOH) is a histogram-based keypoint descriptor that can be associated to multiple quantized rotations of the keypoint patch without any recomputation. This property can be exploited to define the best distance between two descriptor vectors, thus avoiding computing the dominant orientation. In addition, sGLOH can reject incongruous correspondences by adding a global constraint on the rotations either as an a priori knowledge or based on the data. This paper thoroughly reconsiders sGLOH and improves it in terms of robustness, speed and descriptor dimension. The revised sGLOH embeds more quantized rotations, thus yielding more correct matches. A novel fast matching scheme is also designed, which significantly reduces both computation time and memory usage. In addition, a new binarization technique based on comparisons inside each descriptor histogram is defined, yielding a more compact, faster, yet robust alternative. Results on an exhaustive comparative experimental evaluation show that the revised sGLOH descriptor incorporating the above ideas and combining them according to task requirements, improves in most cases the state of the art in both image matching and object recognition
Dissecting and Reassembling Color Correction Algorithms for Image Stitching
No full textThis paper introduces a new compositional framework for classifying color correction methods according to their two main computational units. The framework was used to dissect fifteen among the best color correction algorithms and the computational units so derived, with the addition of four new units specifically designed for this work, were then reassembled in a combinatorial way to originate about one hundred distinct color correction methods, most of which never considered before. The above color correction methods were tested on three different existing datasets, including both real and artificial color transformations, plus a novel dataset of real image pairs categorized according to the kind of color alterations induced by specific acquisition setups. Differently from previous evaluations, special emphasis was given to effectiveness in real world applications, such as image mosaicing and stitching, where robustness with respect to strong image misalignments and light scattering effects is required. Experimental evidence is provided for the first time in terms of the most recent perceptual image quality metrics, which are known to be the closest to human judgment. Comparative results show that combinations of the new computational units are the most effective for real stitching scenarios, regardless of the specific source of color alteration. On the other hand, in the case of accurate image alignment and artificial color alterations, the best performing methods either use one of the new computational units, or are made up of fresh combinations of existing unit
Extending the sGLOH descriptor
No full textThis paper proposes an extension of the sGLOH keypoint descriptor [3] which improves its robustness and discriminability. The sGLOH descriptor can handle discrete rotations by a cyclic shift of its elements thanks to its circular structure, but its performance can decrease when the keypoint relative rotation is in between two sGLOH discrete rotations. The proposed extension couples together two sGLOH descriptors for the same patch with different rotations in order to cope with this issue and it can be also applied straightly to the sCOr and sGOr matching strategies of sGLOH. Experimental results show a consistent improvement of the descriptor discriminability, while different setups can be used to reduce the running time according to the desired tas
An evaluation of recent local image descriptors for real-world applications of image matching
No full textThis paper discusses and compares the best and most recent local descriptors, evaluating them on increasingly complex image matching tasks, encompassing planar and non-planar scenarios under severe viewpoint changes. This evaluation, aimed at assessing descriptor suitability for real-world applications, leverages the concept of approximated overlap error as a means to naturally extend to non-planar scenes the standard metric used for planar scenes. According to the evaluation results, most descriptors exhibit a gradual performance degradation in the transition from planar to non-planar scenes. The best descriptors are those capable of capturing well not only the local image context, but also the global scene structure. Data-driven approaches are shown to have reached the matching robustness and accuracy of the best hand-crafted descriptor
Color Correction for Image Stitching by Monotone Cubic Spline Interpolation
No full textThis paper proposes a novel color correction scheme for image stitching where the color map transfer is modelled by a monotone Hermite cubic spline and smoothly propagated into the target image. A three-segments monotone cubic spline minimizing color distribution statistics and gradient differences with respect to both the source and target images is used. While the spline model can handle non-linear color maps, the minimization over the gradient differences limits strong alterations on the image structure. Adaptive heuristics are introduced to reduce the minimization search space and thus computational time. Experimental comparisons with respect to the state-of-the-art linear mapping models show the validity of the proposed method
Estimating the best reference homography for planar mosaics from videos
No full textThis paper proposes a novel strategy to find the best reference homography in mosaics from video sequences. The reference homography globally minimizes the distortions induced on each image frame by the mosaic homography itself. This method is designed for planar mosaics on which a bad choice of the first reference image frame can lead to severe distortions after concatenating several successive homographies. This often happens in the case of underwater mosaics with non-flat seabed and no georeferential information available. Given a video sequence of an almost planar surface, sub-mosaics with low distortions of temporally close image frames are computed and successively merged according to a hierarchical clustering procedure. A robust and effective feature tracker using an approximated global position map between image frames allows us to build the mosaic also between locally close but not temporally consecutive frames. Sub-mosaics are successively merged by concatenating their relative homographies with another reference homography which minimizes the distortion on each frame of the fused image. Experimental results on challenging real underwater videos show the validity of the proposed method
Which Is Which? Evaluation of Local Descriptors for Image Matching in Real-World Scenarios
No full textMatching with local image descriptors is a fundamental task in many computer vision applications. This paper describes the WISW contest held within the framework of the CAIP 2019 conference, aimed at benchmarking recent descriptors in challenging planar and non-planar real image matching scenarios. According to the contest results, the descriptors submitted to the competition, most of which based on deep learning, perform significantly better than the current state-of-the-art in image matching. Nonetheless, there is still room for improvement, especially in the case of non-planar scene
- …
