Generating octree models of 3D objects from their silhouettes in a sequence of images
Computer Vision, Graphics, and Image Processing
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Model-based object tracking in monocular image sequences of road traffic scenes
International Journal of Computer Vision
The perception of shading and reflectance
Perception as Bayesian inference
The SR-tree: an index structure for high-dimensional nearest neighbor queries
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
The Visual Hull Concept for Silhouette-Based Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Recovering Intrinsic Images from a Single Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
A bayesian approach to image-based visual hull reconstruction
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Detection of moving cast shadows for object segmentation
IEEE Transactions on Multimedia
Hierarchical shadow detection for color aerial images
Computer Vision and Image Understanding
ACM SIGGRAPH 2007 papers
IEICE - Transactions on Information and Systems
Hierarchical shadow detection for color aerial images
Computer Vision and Image Understanding
Robust fast belief propagation for real-time stereo matching
ICACT'09 Proceedings of the 11th international conference on Advanced Communication Technology - Volume 2
Detecting ground shadows in outdoor consumer photographs
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Pixel-Wise histograms for visual segment description and applications
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
Evolutionary algorithm-based background generation for robust object detection
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Background updating for visual surveillance
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Adaptive background generation for video object segmentation
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
Interactive shadow removal from a single image using hierarchical graph cut
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part I
ISIDIS: an intelligent videosurveillance system
Proceedings of the International Working Conference on Advanced Visual Interfaces
Synthetic ground truth dataset to detect shadows cast by static objects in outdoors
Proceedings of the 1st International Workshop on Visual Interfaces for Ground Truth Collection in Computer Vision Applications
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Variation in illumination conditions caused by weather, time of day, etc., makes the task difficult when building video surveillance systems of real world scenes. Especially, cast shadows produce troublesome effects, typically for object tracking from a fixed viewpoint, since it yields appearance variations of objects depending on whether they are inside or outside the shadow. In this paper, we handle such appearance variations by removing shadows in the image sequence. This can be considered as a preprocessing stage which leads to robust video surveillance. To achieve this, we propose a framework based on the idea of intrinsic images. Unlike previous methods of deriving intrinsic images, we derive time-varying reflectance images and corresponding illumination images from a sequence of images instead of assuming a single reflectance image. Using obtained illumination images, we normalize the input image sequence in terms of incident lighting distribution to eliminate shadowing effects. We also propose an illumination normalization scheme which can potentially run in real time, utilizing the illumination eigenspace, which captures the illumination variation due to weather, time of day, etc., and a shadow interpolation method based on shadow hulls. This paper describes the theory of the framework with simulation results and shows its effectiveness with object tracking results on real scene data sets.