Motion detection plays an important role in most video based applications. One of the many possible ways to detect motion consists in background subtraction. This paper discusses experiments led for ...a particular background subtraction technique called ViBe. This technique models the background with a set of samples for each pixel and compares new frames, pixel by pixel, to determine if a pixel belongs to the background or to the foreground. In its original version, the scope of ViBe is limited to background modeling. In this paper, we introduce a series of modifications that alter the working of ViBe, like the inhibition of propagation around internal borders or the distinction between the updating and segmentation masks, or process the output, for example by some operations on the connected components. Experimental results obtained for video sequences provided on the workshop site validate the improvements of the proposed modifications.
Understanding broadcast videos is a challenging task in computer vision, as it requires generic reasoning capabilities to appreciate the content offered by the video editing. In this work, we propose ...SoccerNet-v2, a novel large-scale corpus of manual annotations for the SoccerNet 24 video dataset, along with open challenges to encourage more research in soccer understanding and broadcast production. Specifically, we release around 300k annotations within SoccerNet's 500 untrimmed broadcast soccer videos. We extend current tasks in the realm of soccer to include action spotting, camera shot segmentation with boundary detection, and we define a novel replay grounding task. For each task, we provide and discuss benchmark results, reproducible with our open-source adapted implementations of the most relevant works in the field. SoccerNet-v2 is presented to the broader research community to help push computer vision closer to automatic solutions for more general video understanding and production purposes.
Background
Double‐blind, placebo‐controlled food challenge (DBPCFC) is considered the gold standard for food allergy diagnosis. However, this test is rarely performed routinely in clinical practice ...because of various practical issues, e.g. the lack of a standardized matrix preparation. The aim of this study was to develop and validate a convenient DBPCFC matrix, that can easily be implemented in daily clinical practice. The focus of this study was the blinding of hazelnuts, whereby the hazelnuts retained as much as possible their allergenicity and could be mixed homogenously in low‐doses to the matrices.
Methods
A basophil‐activation test (BAT), microbial tests and an LC‐MS/MS test were performed to assess respectively the allergenicity of the used hazelnuts, the microbial stability of the novel developed matrices and the homogeneity of the hazelnuts in the matrices. A sensory test was conducted to validate the blinding of the hazelnuts in the matrices. A pilot DBPCFC study included eight patients as proof of concept.
Results
The BAT‐test gave the first insights concerning the retained allergenicity of the hazelnuts. The microbial safety could be assured after 12 months of storage. Sufficient masking was assessed by several sensory tests. Homogeneous hazelnut distribution could be achieved for the different hazelnut concentrations. The DBPCFC's results showed diverse allergic responders (from no reactions to distinct objective symptoms).
Conclusion
A novel stable and validated DBPCFC matrix using raw hazelnuts has been developed that allows easy preparation in a standardized way for convenient use in daily clinical practice.
Trial registration EC Project number: EC/2015/0852; Date of registration: 13 Oct 2015; End date: 01 Feb 2017
Ship-based automatic detection of small floating objects on an agitated sea surface remains a hard problem. Our main concern is the detection of floating mines, which proved a real threat to shipping ...in confined waterways during the first Gulf War, but applications include salvaging, search-and-rescue operation, perimeter, or harbour defense. Detection in infrared (IR) is challenging because a rough sea is seen as a dynamic background of moving objects with size order, shape, and temperature similar to those of the floating mine. In this paper we have applied a selection of background subtraction algorithms to the problem, and we show that the recent algorithms such as ViBe and behaviour subtraction, which take into account spatial and temporal correlations within the dynamic scene, significantly outperform the more conventional parametric techniques, with only little prior assumptions about the physical properties of the scene.
Several efficient algorithms for computing erosions and openings have been proposed recently.
They improve on VAN HERK's algorithm in terms of number of comparisons for large structuring
elements. In ...this paper we introduce a theoretical framework of anchors that aims at a better
understanding of the process involved in the computation of erosions and openings. It is shown
that the knowledge of opening anchors of a signal f is sufficient to perform both the erosion and
the opening of f.
Then we propose an algorithm for one-dimensional erosions and openings which exploits
opening anchors. This algorithm improves on the fastest algorithms available in literature by
approximately 30% in terms of computation speed, for a range of structuring element sizes and
image contents
The impact of low-oxygen spiral-filter press technology combined with thermal pasteurization (TP), pulsed electric field (PEF) and high pressure processing (HPP) on cloudy apple juice quality was ...investigated immediately after the treatments and after 3 weeks of storage at 4 °C. Based on equivalent levels of microbial safety and desired shelf-life, low and high processing intensities were selected: TP (72 °C/15 s; 85 °C/30 s), PEF (12.5 kV/cm, 76.4 kJ/L; 12.3 kV/cm, 132.5 kJ/L), and HPP (400 MPa/3 min; 600 MPa/3 min). High intensity thermal treatment resulted in a bright, yellowish color which was maintained during storage. PPO and POD activities were largely reduced by high intensity PEF and TP yet showed high resistance to HPP. The highest vitamin C content was provided by fresh juice followed by PEF-treated juices. Due to oxidative degradation reactions, vitamin C of all treated samples significantly decreased during storage. Immediately after processing, high cloud stability values were obtained in all samples; however, cloud stability decreased during storage particularly for HPP juices with high residual PME. No significant changes were observed in pH, titratable acidity, organic acid and sugar content which also corresponded to sweet and sour taste. Results from untargeted volatile profiles showed that esters increased after PEF and were better retained after HPP. Contrary to TP treatment where ester degradation reactions occurred together with the formation of off-flavors. Most of the volatiles decreased during storage which could be linked to oxidation and ester hydrolysis reactions.
Being one of the most popular fruit juices consumed worldwide, cloudy apple juice can still undergo quality changes such as color degradation, cloud loss (fast sedimentation) and flavor changes during processing and storage. This study evaluates the potential of low-oxygen spiral-filter press in combination with different preservation technologies to obtain a maximal quality of cloudy apple juice. Results showed that high intensity thermal pasteurization can effectively inactivate quality-degrading enzymes, therefore it is useful to obtain an optimal cloudy apple juice product in terms of color and cloud stability. Although HPP has minimal impact on aroma of the juice, shelf-life of the juice may be limited due to incomplete enzyme inactivation. In the case of PEF treatment, thermal effects may contribute to maintain apple juice quality.
•Enzymes can be completely inactivated by high intensity thermal processing.•Less effect of processing and storage on particle sizes, acidity and sugar content•Spiral-filter press combined with PEF or HPP retained the fresh apple juice aroma.•Spiral-filter press coupled with severe pasteurization preserved color and cloud stability.•Thermal effects resulting from PEF may contribute in maintaining the juice quality.
Extracts of 31 leek cultivars were analyzed using liquid chromatography–tandem mass spectrometry (HPLC-MS/MS) to determine the distribution of the two most abundant S-alk(en)yl-l-cysteine sulfoxides ...(ACSOs) in leek, that is, isoalliin and methiin. The isoalliin concentration of the white shaft and green leaves of the 31 leek cultivars varied from 15 to 53 mg/g dry weight (dw) and from 9 to 45 mg/g dw, respectively, whereas the methiin concentration varied from 3 to 16 mg/g dw and from 1 to 10 mg/g dw, respectively. Leek cultivar and tissue had an effect on the ACSO amounts. Cultivars Artico and Apollo F1 rated highest for the mean isoalliin and methiin concentration, respectively. In general, the whole leek plant of the winter leek cultivars contained a significantly higher ACSO amount than the summer and autumn cultivars. To determine whether this difference was attributed to the cultivar background or time of harvest, ACSOs were also quantitated in nine leek hybrids at four different stages during the next growth season. The amounts of ACSO changed significantly during the growth season, indicating the importance of harvest at specific time moments, although there was still an effect of cultivar on the ACSO amounts.
Deep learning has emerged as an effective solution for solving the task of object detection in images but at the cost of requiring large labeled datasets. To mitigate this cost, semi-supervised ...object detection methods, which consist in leveraging abundant unlabeled data, have been proposed and have already shown impressive results. However, most of these methods require linking a pseudo-label to a ground-truth object by thresholding. In previous works, this threshold value is usually determined empirically, which is time consuming, and only done for a single data distribution. When the domain, and thus the data distribution, changes, a new and costly parameter search is necessary. In this work, we introduce our method Adaptive Self-Training for Object Detection (ASTOD), which is a simple yet effective teacher-student method. ASTOD determines without cost a threshold value based directly on the ground value of the score histogram. To improve the quality of the teacher predictions, we also propose a novel pseudo-labeling procedure. We use different views of the unlabeled images during the pseudo-labeling step to reduce the number of missed predictions and thus obtain better candidate labels. Our teacher and our student are trained separately, and our method can be used in an iterative fashion by replacing the teacher by the student. On the MS-COCO dataset, our method consistently performs favorably against state-of-the-art methods that do not require a threshold parameter, and shows competitive results with methods that require a parameter sweep search. Additional experiments with respect to a supervised baseline on the DIOR dataset containing satellite images lead to similar conclusions, and prove that it is possible to adapt the score threshold automatically in self-training, regardless of the data distribution. The code is available at https:// github.com/rvandeghen/ASTOD
Background subtraction is usually based on low-level or hand-crafted features such as raw color components, gradients, or local binary patterns. As an improvement, we present a background subtraction ...algorithm based on spatial features learned with convolutional neural networks (ConvNets). Our algorithm uses a background model reduced to a single background image and a scene-specific training dataset to feed ConvNets that prove able to learn how to subtract the background from an input image patch. Experiments led on 2014 ChangeDetection.net dataset show that our ConvNet based algorithm at least reproduces the performance of state-of-the-art methods, and that it even outperforms them significantly when scene-specific knowledge is considered.
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