Results 211 to 220 of about 29,954 (261)

A survey of cast shadow detection algorithms

Pattern Recognition Letters, 2012
Cast shadows need careful consideration in the development of robust dynamic scene analysis systems. Cast shadow detection is critical for accurate object detection in video streams, and their misclassification can cause errors in segmentation and tracking.
Jyoti Singhai, Nijad Al-Najdawi
exaly   +2 more sources

Detecting shadow lobbying [PDF]

Social Network Analysis and Mining, 2022
Lobbying activity is subject to strict disclosure requirements in the USA. Failure to comply with these requirements can lead to criminal and civil penalties. It is claimed that these tight lobbying disclosure measures resulted in an increase in ‘underground lobbying’.
Ivan Slobozhan, Peter Ormosi, Rajesh Sharma 0002   +2 more
openaire   +2 more sources

Shadow Detection via Predicting the Confidence Maps of Shadow Detection Methods

Proceedings of the 29th ACM International Conference on Multimedia, 2021
Today's mainstream shadow detection methods are manually designed via a case-by-case approach. Accordingly, these methods may only be able to detect shadows for specific scenes. Given the complex and diverse shadow scenes in reality, none of the existing methods can provide a one-size-fits-all solution with satisfactory performance.
Jingwei Liao, Yanli Liu 0002, Guanyu Xing, Housheng Wei, Jueyu Chen, Songhua Xu   +5 more
openaire   +1 more source

Robust Shadow Detection by Exploring Effective Shadow Contexts

Proceedings of the 29th ACM International Conference on Multimedia, 2021
Effective contexts for separating shadows from non-shadow objects can appear in different scales due to different object sizes. This paper introduces a new module, Effective-Context Augmentation (ECA), to utilize these contexts for robust shadow detection with deep structures.
Xianyong Fang, Xiaohao He, Linbo Wang 0001, Jianbing Shen   +3 more
openaire   +1 more source

Kinect Shadow Detection and Classification

2013 IEEE International Conference on Computer Vision Workshops, 2013
Kinect depth maps often contain missing data, or "holes", for various reasons. Most existing Kinect-related research treat these holes as artifacts and try to minimize them as much as possible. In this paper, we advocate a totally different idea - turning Kinect holes into useful information. In particular, we are interested in the unique type of holes
Teng Deng, Hui Li, Jianfei Cai 0001, Tat-Jen Cham, Henry Fuchs   +4 more
openaire   +1 more source

Detection of vehicles in shadow areas

2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2011
This paper presents a new method to automatically detect occluded vehicle in semi or deep shadow areas using combined very high resolution (VHR) 3D LIDAR and hyperspectral data. The proposed shape/spectral integration (SSI) decision fusion algorithm was shown to outperform the spectral based anomaly algorithm mainly in deep shadow areas.
Michal Shimoni, Gustav Tolt, Christiaan Perneel, Jörgen Ahlberg   +3 more
openaire   +1 more source

Exploiting Residual and Illumination with GANs for Shadow Detection and Shadow Removal

ACM Transactions on Multimedia Computing, Communications, and Applications, 2023
Residual image and illumination estimation have been proven to be helpful for image enhancement. In this article, we propose a general framework, called RI-GAN, that exploits residual and illumination using generative adversarial networks (GANs). The proposed framework detects and removes shadows in a coarse-to-fine fashion.
Ling Zhang, Chengjiang Long, Xiaolong Zhang, Chunxia Xiao   +3 more
openaire   +1 more source

Distraction-Aware Shadow Detection

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Shadow detection is an important and challenging task for scene understanding. Despite promising results from recent deep learning based methods. Existing works still struggle with ambiguous cases where the visual appearances of shadow and non-shadow regions are similar (referred to as distraction in our context).
Quanlong Zheng, Xiaotian Qiao, Ying Cao 0001, Rynson W. H. Lau   +3 more
openaire   +1 more source

Shadow detection and removal using a shadow formation model

2016 IEEE First International Conference on Data Stream Mining & Processing (DSMP), 2016
This work is devoted to shadow detection and removal from very high resolution (VHR) satellite images. As an example, a WorldView-2 satellite image of an urban area was processed. The presence of shadows can cause a loss of a significant part of useful information.
Yana I. Shedlovska, Volodymyr V. Hnatushenko   +1 more
openaire   +1 more source

Shadow-aware decomposed transformer network for shadow detection and removal

Pattern Recognition
, Xiao Wang
exaly   +2 more sources