Physical models for moving shadow and object detection in video

By Sohail Nadimi, Bir Bhanu. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004

320 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Individual recognition using gait energy image (2006, background): “Note that a moving object detection approach can also provide information about the material type on which a person is walking [10].”
A Multi-Task Mean Teacher for Semi-Supervised Shadow Detection (2020, unknown): “, image segmentation [4], object detection [2], and object tracking [27].”
DeshadowNet: A Multi-context Embedding Deep Network for Shadow Removal (2017, background): “The presence of illumination changes in an image, shadows in particular, have been proved to be one of the main challenging factors for a variety of computer vision tasks, such as object detection and tracking [6, 24].”
SAM-Adapter: Adapting Segment Anything in Underperformed Scenes (2023, background): “They can also negatively impact the performance of computer vision tasks [39, 9].”
Shadow detection: A survey and comparative evaluation of recent methods (2012, background): “Physical properties The linear attenuation model assumes that the illumination source produces pure white light [24], which is often not the case.”