Results 261 to 270 of about 21,066 (308)

Foreground Object Sensing for Saliency Detection

Proceedings of the 2016 ACM on International Conference on Multimedia Retrieval, 2016
Many state-of-the-art saliency detection algorithms rely on the boundary prior, but these algorithms simply suppose the boundaries around an image as background regions. Here we propose a fast and effective algorithm for salient object detection. First, a novel method is proposed to approximately locate the foreground object by using the convex hull ...
Hengliang Zhu, Bin Sheng 0001, Xiao Lin 0012, Yangyang Hao, Lizhuang Ma   +4 more
openaire   +1 more source

Deep Variation Transformation Network for Foreground Detection

IEEE Transactions on Circuits and Systems for Video Technology, 2021
In existing literature, the distribution of pixel observations is analyzed with models designed for the video foreground detection task. However, it is possible that the background and foreground share similar observations, causing false detections.
Yongxin Ge, Junyin Zhang, Xinyu Ren, Chenqiu Zhao, Juan Yang, Anup Basu   +5 more
openaire   +1 more source

Background/Foreground Detection

2011
With the acquisition of an image, the first step is to distinguish objects of interest from the background. In surveillance applications, those objects of interest are usually humans. Their various shapes and different motions, including walking, jumping, bending down, and so forth, represent significant challenges in the extraction of foreground ...
Huihuan Qian, Xinyu Wu, Yangsheng Xu
openaire   +1 more source

Hierarchical Foreground Detection in Dynamic Background

2011
Foreground detection in dynamic background is one of challenging problems in many vision-based applications. In this paper, we propose a hierarchical foreground detection algorithm in the HSL color space. With the proposed algorithm, the experimental precision in five testing sequences reached to 56.46%, which was the best among compared four methods.
Guoliang Lu, Mineichi Kudo, Jun Toyama
openaire   +1 more source

Stationary foreground detection for video-surveillance based on foreground and motion history images

2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance, 2013
Stationary foreground detection is a common stage in many video-surveillance applications. In this paper, we propose an approach for stationary foreground detection in video based on the spatio-temporal variation of foreground and motion data. Foreground data are obtained by Background Subtraction to detect regions of interest.
Diego Ortego, Juan C. SanMiguel
openaire   +1 more source

Foreground detection by ensembles of random polygonal tilings

Expert Systems with Applications, 2020
Abstract In this work a novel region-based approach for the detection of foreground in video sequences is presented. The model consists of an ensemble of layers or tilings, where each tiling represents, by means of randomly chosen parallelogram regions, the background of the scene.
Miguel A. Molina-Cabello, David A. Elizondo, Rafael M. Luque-Baena, Ezequiel López-Rubio   +3 more
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Simultaneous Foreground Detection and Classification with Hybrid Features

2015 IEEE International Conference on Computer Vision (ICCV), 2015
In this paper, we propose a hybrid background model that relies on edge and non-edge features of the image to produce the model. We encode these features into a coding scheme, that we called Local Hybrid Pattern (LHP), that selectively models edges and non-edges features of each pixel.
Jaemyun Kim, Adín Ramírez Rivera, Byungyong Ryu, Oksam Chae   +3 more
openaire   +1 more source

Evaluation of foreground detection methodology for a moving camera

2015 21st Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV), 2015
Detection of moving objects is one of the key steps for vision based applications. Many previous works leverage background subtraction using background models and assume that image sequences are captured from a stationary camera. These methods are not directly applied to image sequences from a moving camera because both foreground and background ...
Tsubasa Minematsu, Hideaki Uchiyama, Atsushi Shimada 0001, Hajime Nagahara, Rin-Ichiro Taniguchi   +4 more
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A Framework for Foreground Detection in Complex Environments

2004
In this paper, a framework is proposed for the foreground detection in various complex environments. This method integrates the detection and tracking procedures into a unified probability framework by considering the spatial, spectral and temporal information of pixels to model different complex backgrounds.
Junxian Wang, How-Lung Eng, Alvin Harvey Kam, Wei-Yun Yau   +3 more
openaire   +1 more source

Foreground Gated Network for Surveillance Object Detection

2018 IEEE Fourth International Conference on Multimedia Big Data (BigMM), 2018
Object detection in surveillance videos is challenging due to the requirement of real-time detection of small objects in presence of motion blurs and over-exposures at night. False positives caused by above challenges on background areas are more critical in surveillance videos compared to general object detection.
Zhihang Fu, Chang Zhou, Hongwei Yong, Rongxin Jiang 0001, Xiang Tian 0002, Yaowu Chen, Xian-Sheng Hua 0001   +6 more
openaire   +1 more source