公开(公告)号：US20230394877A1

公开(公告)日：2023-12-07

申请号：US18205226

申请日：2023-06-02

Applicant: Northeastern University

Inventor： Sarah OSTADABBAS ,  Emily ZIMMERMAN ,  Xiaofei HUANG ,  Michael WAN

IPC: G06V40/16 ,  G06V10/82 ,  G06V10/774 ,  G06V20/70

CPC classification number: G06V40/172 ,  G06V10/82 ,  G06V40/171 ,  G06V10/774 ,  G06V20/70

Abstract: Provided herein are methods and systems for identifying a face of an infant in an image including providing a computer comprising a processor and a memory trained with a set of training images and programmed with a convolutional neural network (CNN) model for identifying a face of an infant in a test image suspected of comprising an infant's face, wherein each image of the set of training images includes a plurality of facial landmark annotations and at least one pose attribute annotation, providing a test image suspected of comprising an image of an infant's face, and processing the test image using the computer, whereby the infant's face is identified in the test image.

公开(公告)号：US20250111672A1

公开(公告)日：2025-04-03

申请号：US18903566

申请日：2024-10-01

Applicant: Northeastern University

Inventor： Sarah OSTADABBAS ,  Emily ZIMMERMAN ,  Michael WAN ,  Elaheh HATAMIMAJOUMERD ,  Shaotong ZHU

IPC: G06V20/40 ,  G06T7/246 ,  G06V10/774 ,  G06V40/16 ,  G06V40/20

Abstract: Provided herein are methods and systems for detecting non-nutritive sucking (NNS) by an infant in a video recording and determining the start and end times of the NNS. The NNS detection method includes creating video segments from the video recording. For each video segment, action recognition is performed that includes determining a face bounding box for each frame of the video segment. The frames are cropped based on the bounding box. For each cropped frame, an optical flow frame is generated of the optical flow direction vectors for pixels of the cropped frame. Using a convolution network and the optical flow frames, a segment feature vector is determined from the pre-classification feature layer of the convolution network. The segment feature vector corresponding to each video segment is used as input to a dilated convolution network to predict an NNS action and determine the start and end time of the NNS.