Results 251 to 260 of about 2,939,416 (298)

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   +2 more sources

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

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

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   +2 more sources

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 Detecting and Shadow Interpolation Algorithm for InSAS

Advanced Materials Research, 2012
The shadow detecting algorithm based on the coherence and the Sigma filter is used to pick up the shadow of interferometric synthetic aperture sonar (InSAS), which can eliminate small separated shadow areas. To solve the problems such as great computer complexity of traditional Shepard interpolation method and large fluctuant of linear interpolation ...
Sen Zhang, Ming Chen, Jin Song Tang
openaire   +1 more source

A texture-based approach for shadow detection

Proceedings. IEEE Conference on Advanced Video and Signal Based Surveillance, 2005., 2006
Shadows detection is a fundamental step in visual surveillance and monitoring systems. Shadow points are often misclassified as object points causing errors in localization, segmentation, measurements, tracking and classification of moving objects. In order to detect potential shadow points an automatic segmentation procedure is performed and, for all ...
A Leone, C Distante, F Buccolieri
openaire   +3 more sources

Shadow Detection and Removal Using GAN

2020 28th European Signal Processing Conference (EUSIPCO), 2021
To remove shadowed region in a single image, it is important to obtain high accuracy in both two processes, shadow detection and removal. In order to improve the results, recent methods perform these two processes simultaneously and use GAN for the training.
Takahiro Nagae, Ryo Abiko, Takuro Yamaguchi, Masaaki Ikehara   +3 more
openaire   +2 more sources

Robust road detection in shadow conditions

Journal of Electronic Imaging, 2016
Image-based road detection is a vital task for many real-world applications, such as autonomous driving and obstacle detection. We propose a method for segmenting road regions from a single image based on horizon line estimation and clustering technology.
Kaiyue Lu, Siyu Xia, Junkang Zhang, A. K. Qin 0001   +3 more
openaire   +2 more sources

Accelerated Shadow Detection and Removal Method

2019 IEEE/ACS 16th International Conference on Computer Systems and Applications (AICCSA), 2019
Shadows can have a negative effect on the ability of computer vision techniques for object detection, tracking, and recognition. Therefore, ability to remove shadows and byproducts of illumination is an important problem to enable effective object recognition actions. As applications move into levels of higher information extraction and higher required
Edward Richter, Ryan Raettig, Joshua Mack, Spencer Valancius, Burak Unal, Ali Akoglu   +5 more
openaire   +1 more source