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1. (WO2018084942) DEEP CROSS-CORRELATION LEARNING FOR OBJECT TRACKING

Pub. No.:    WO/2018/084942    International Application No.:    PCT/US2017/052252
Publication Date: Sat May 12 01:59:59 CEST 2018 International Filing Date: Wed Sep 20 01:59:59 CEST 2017
IPC: G06N 3/04
G06N 3/08
G06K 9/32
Applicants: QUALCOMM INCORPORATED
Inventors: HABIBIAN, Amirhossein
SNOEK, Cornelis, Gerardus, Maria
Title: DEEP CROSS-CORRELATION LEARNING FOR OBJECT TRACKING
Abstract:
An artificial neural network for learning to track a target across a sequence of frames includes a representation network configured to extract a target region representation from a first frame and a search region representation from a subsequent frame. The artificial neural network also includes a cross-correlation layer configured to convolve the extracted target region representation with the extracted search region representation to determine a cross-correlation map. The artificial neural network further includes a loss layer configured to compare the cross-correlation map with a ground truth cross-correlation map to determine a loss value and to back propagate the loss value into the artificial neural network to update filter weights of the artificial neural network.