Results 11 to 20 of about 21,066 (308)
Foreground Feature Enhancement for Object Detection [PDF]
IEEE Access, 2019 Deep convolutional neural networks have shown great success in object detection. Most object detection methods focus on improving network architecture and introducing additional objective functions to improve the discrimination of object detectors, while
Shenwang Jiang +4 more
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Fuzzy foreground detection for infrared videos [PDF]
2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008 International audienceWe present a foreground detection algorithm based on a fuzzy integral that is particularly suitable for infrared videos. The proposed detection of moving objects is based on fusing intensity and textures using fuzzy integral.
Fida El Baf +5 more
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An edge-based approach for robust foreground detection [PDF]
, 2011 Foreground segmentation is an essential task in many image processing applications and a commonly used approach to obtain foreground objects from the background.
Grünwedel, Sebastian +5 more
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Spatiotemporal saliency estimation by spectral foreground detection
IEEE Transactions on Multimedia, 2018 We present a novel approach for spatiotemporal saliency detection by optimizing a unified criterion of color contrast, motion contrast, appearance, and background cues. To this end, we first abstract the video by temporal superpixels.
Kiranyaz, Mustafa Serkan +5 more
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Foreground Detection Based on Superpixel and Semantic Segmentation. [PDF]
Comput Intell Neurosci, 2022 Foreground detection is an essential step in computer vision and video processing. Accurate foreground object extraction is crucial for subsequent high-level tasks such as target recognition and tracking. Although many foreground detection algorithms have been proposed, foreground detection in complex scenes is still a challenging problem.
Feng J, Liu P, Kim YK.
europepmc +3 more sources
Foreground detection in camouflaged scenes [PDF]
2017 IEEE International Conference on Image Processing (ICIP), 2017 IEEE International Conference on Image Processing ...
Shuai Li 0005 +4 more
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Foreground Detection Using the Choquet Integral [PDF]
2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services, 2008 Foreground Detection is a key step in background subtraction problem. This approach consists in the detection of moving objects from static cameras through a classification process of pixels as foreground or background. The presence of some critical situations i.e noise, illumination changes and structural background changes produces an uncertainty in ...
Fida El Baf +2 more
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Generation of Background Model Image Using Foreground Model
IEEE Access, 2021 Proper consideration of the temporal domain and the spatial domain is essential to perform robust foreground object detection in visual surveillance. However, there are difficulties in considering long-term temporal information with CNN-based methods. To
Jae-Yeul Kim, Jong-Eun Ha
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Bayesian background modeling for foreground detection [PDF]
Proceedings of the third ACM international workshop on Video surveillance & sensor networks, 2005 We propose a Bayesian learning method to capture the background statistics of a dynamic scene. We model each pixel as a set of layered normal distributions that compete with each other. Using a recursive Bayesian learning mechanism, we estimate not only the mean and variance but also the probability distribution of the mean and covariance of each model.
Fatih Porikli, Oncel Tuzel
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RGB-D Image Saliency Detection via Background and Foreground Fusion
Jisuanji kexue yu tansuo, 2020 RGB-D image saliency detection refers to the addition of depth information in traditional 2D images to extract significant objects. However, for current saliency detection models, most of them focus on the saliency objects themselves, but ignore the ...
ZHAO Qiang, WANG Aiping, LIU Zhengyi
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