The present invention relates to the technical field of object recognition. A training method for object recognition from top-view images uses a step of labelling at least one training object from at least one training image using a pre-defined labelling scheme. A detection method for object recognition uses a step of applying a test window on a test image. An object recognition method comprises the training method and the detection method. A surveillance system performs the detection method. The present invention is particularly useful for object recognition in optic-distorted videos based on a machine training method. The invention is further particularly useful for person detection from top-view visible imagery and surveillance and presence monitoring in a region of interest (ROI).

Training method and detection method for object recognition / Kaestle, Herbert; Brandlmaier, Meltem Demirkus; Galasso, Fabio; Wang, Ling. - (2016).

Training method and detection method for object recognition

GALASSO, Fabio;
2016

Abstract

The present invention relates to the technical field of object recognition. A training method for object recognition from top-view images uses a step of labelling at least one training object from at least one training image using a pre-defined labelling scheme. A detection method for object recognition uses a step of applying a test window on a test image. An object recognition method comprises the training method and the detection method. A surveillance system performs the detection method. The present invention is particularly useful for object recognition in optic-distorted videos based on a machine training method. The invention is further particularly useful for person detection from top-view visible imagery and surveillance and presence monitoring in a region of interest (ROI).
2016
Computer vision; Machine Learning; Detection; Recognition
05 Brevetto::05a Brevetto
Training method and detection method for object recognition / Kaestle, Herbert; Brandlmaier, Meltem Demirkus; Galasso, Fabio; Wang, Ling. - (2016).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1341901
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