1,162 research outputs found
View synthesis along a curve from two uncalibrated views
No full textThis paper presents a generic framework for novel view synthesis from two uncalibrated reference views that allows to move a virtual camera along a curve that is obtained starting from the epipolar geometry of the reference views. The scene is described by its relative affine structure from which novel views are extrapolated and interpolated. The main contribution of this paper is an automatic method for specifying virtual camera locations in an uncalibrated setting. Experiments with synthetic and real images illustrate the approach
Corrigendum to “Performance of Candida albicans germ tube antibodies (CAGTA) and its association with (1 → 3)-β-D-glucan (BDG) for diagnosis of invasive candidiasis (IC)” (Diagnostic Microbiology & Infectious Disease (2019) 93(1) (39–43), (S073288931830230X), (10.1016/j.diagmicrobio.2018.07.007))
No full textIn the article “Performance of Candida albicans germ tube antibodies (CAGTA) and its association with (1 → 3)-β-D-glucan (BDG) for diagnosis of invasive candidiasis (IC),” the authors’ names are listed incorrectly. The correct names are as follows: Pietro Pini, Bruna Colombari, Enrico Marchi, Anna Castagnoli, Claudia Venturelli, Mario Sarti, Elisabetta Blasi
Uncalibrated Interpolation of Rigid Displacements for View Synthesis
No full textIn this paper we present a method for novel view synthesis from two uncalibrated reference views. Snapshots of a scene are created as if they were taken from a different "virtual" viewpoint. The relative affine structure is used to describe the geometry of the scene and then to extrapolate and interpolate novel views. The contribution of this paper is an automatic method for specifying the virtual viewpoint in an uncalibrated setting, based on the interpolation and extrapolation of the epipolar geometry linking the reference views. Experimental results using synthetic and real images are shown
Patch-based background initialization in heavily cluttered video
No full textIn this paper, we propose a patch-based technique for robust background initialization that exploits both spatial and temporal consistency of the static background. The proposed tech- nique is able to cope with heavy clutter, i.e, foreground objects that stand still for a considerable portion of time. First, the sequence is subdivided in patches that are clustered along the time-line in order to narrow down the number of background candidates. Then, a tessellation is grown incrementally by selecting at each step the best continuation of the current background. The method rests on sound principles in all its stages and only few, intelligible parameters are needed. Experimental results show that the pro- posed algorithm is effective and compares favorably with existing techniques
Background Initialization in Cluttered Sequences
No full textIn this paper we propose a technique to robustly estimate the background in a cluttered sequence, i.e., a sequence where occluding objects persist in the same position for a considerable portion of time. As pixel-level heuristic are not sufficient in this case, we introduce spatial support. First the sequence is subdivided in patches that are clustered along the time-line in order to narrow down the number of background candidates. Then the background is grown incrementally by selecting at each step the best continuation of the current background, according to the principles of visual grouping. The method rests on sound principles in all its stages, and only few, intelligible parameters are needed. Experiments with real sequences illustrate the approach
Continuous Parallax Adjustment for 3D-TV
No full textThis paper presents a method to continuously adjust the parallax in 3D-TV visualization. It is based on a generic framework for novel view synthesis from two uncalibrated reference views that allows to move a virtual camera along a path that is obtained starting from the epipolar geometry of the reference views. The scene is described by its relative affine structure from which novel views are extrapolated and interpolated. The main contribution of this paper is an automatic method for specifying virtual camera locations in an uncalibrated setting. Experiments with synthetic and real images illustrate the approach
Video Objects Segmentation by Robust Background Modeling
No full textThis paper deals with the problem of segmenting a video shot into a background (still) mosaic and one or more foreground moving objects. The method is based on ego-motion compensation and background estimation. In order to be able to cope with sequences where occluding objects persist in the same position for a considerable portion of time, the papers concentrates on robust background estimation method. First the sequence is subdivided in patches that are clustered along the time-line in order to narrow down the number of background candidates. Then the background is grown incrementally by selecting at each step the best continuation of the current background, according to the principles of visual grouping. The method rests on sound principles in all its stages, and only few, intelligible parameters are needed. Experiments with real sequences illustrate the approac
Segmentation and tracking of multiple video objects
No full textThis paper describes a technique that produces a content-based representation of a video shot composed by a background (still) mosaic and one or more foreground moving objects. Segmentation of moving objects is based on ego-motion compensation and on background modelling using tools from robust statistics. Region matching is carried out by an algorithm that operates on the Mahalanobis distance between region descriptors in two subsequent frames and uses singular value decomposition to compute a set of correspondences satisfying both the principle of proximity and the principle of exclusion. The sequence is represented as a layered graph, and specific techniques are introduced to cope with crossing and occlusion. Examples of MPEG-4 (Main Profile) encoding are reported
Exemplar-based Background Model lnitialization
No full textMost of the automated video-surveillance applications are based on background (BG) subtraction techniques, that aim at distinguishing moving objects in a static scene. These strategies strongly depend on the BG model, that has to be initialized and updated. A good initialization is crucial for the successive processing. In this paper, we propose a novel method for BG initialization and recovery, that merges interesting ideas coming from the video inpainting and the generative modelling subfields. The method takes as input a video sequence, in which several objects move in front of a stationary BG. Then, a statistical representation of the BG is iteratively built, discarding the moving objects in a fully automatic way. The method is based on the following hypotheses: (i) a portion of the BG, called sure BG, can be identified with high certainty by using only per-pixel reasoning and (ii) the remaining scene BG can be generated utilizing exemplars of the sure BG. The proposed algorithm is able to exploit these hypotheses in a principled and effective way
Citizen science at school increases awareness of biological invasions and contributes to the detection of exotic ambrosia beetles
No full textThe serious and growing threat posed by biological invasions to biodiversity and livelihoods means that public engagement in dealing with problems of invasive alien species is ever more urgent and necessary hence a citizen science experiment was carried out in north-eastern Italy. The study aimed i) to raise awareness of invasive alien species threatening trees and forests, and ii) to perform monitoring activities of a group of wood borers as an example, involving teachers and students (aged 11 to 18) of high schools. Students and teachers were given background knowledge and trained about the protocol for collecting data in schoolyards/grounds. Native (Anisandrus dispar (Fabricius, 1792), Xyleborinus saxesenii (Ratzeburg, 1837)) and exotic ambrosia beetles (Anisandrus maiche Kurentsov, Cnestus mutilatus (Blandford), Xylosandrus crassiusculus (Motschulsky, 1866), Xylosandrus germanus (Blandford, 1894)) were used as the target species, as they could be easily detected through accessible and low-cost traps requiring limited effort. The traps were exposed for 24 hours weekly between March and June 2021. The experiment also aimed to strengthen public involvement, connecting environmental education and experiential outdoor learning. The mutual collaboration resulted in a wider knowledge of the potential impact of exotic species. It also led to new geographical citizen-science records of two alien ambrosia beetles considered to be quarantine pests by the European Union: C. mutilatus, new for the European part of the EPPO (European and Mediterranean Plant Protection Organization) region, and A. maiche, which was previously found only in Eastern European EPPO member countries
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