SALIENT OBJECT DETECTION METHOD AND SYSTEM FOR WEAK SUPERVISION-BASED SPATIO-TEMPORAL CASCADE NEURAL NETWORK

WIPO Patent Application WO/2019/136591

A1

Provided is a salient object detection method for use in the field of video and image recognition, wherein a spatio-temporal cascade neural network comprises a first full convolutional network and a second full convolutional network; the method comprises: inputting a current frame image of a video to be detected into the first full convolutional network to obtain a spatial prior image (S1); generating a temporal prior image according the current frame image and an optical flow image thereof (S2); performing an element operation on the spatial prior image and the temporal prior image to obtain a spatio-temporal prior image (S3); and inputting the spatio-temporal prior image and the next frame image into the second full convolutional network to obtain a spatio-temporal salient image (S4). When detecting a salient object of a video which has a complex scene, spatial prior information of a video frame image and optical flow-based time prior information are integrated, thus achieving the elimination of static salient regions and the generation of the final spatio-temporal salient image within a dynamic scene, such that more abundant information may be acquired within the dynamic scene, thus improving accuracy and robustness.

LUO HAILI (CN)
TANG YI (CN)
ZOU WENBIN (CN)
LI XIA (CN)
XU CHEN (CN)

PCT/CN2018/071902

July 18, 2019

January 09, 2018

Click for automatic bibliography generation  

UNIV SHENZHEN (CN)

G06T7/20; G06T5/00

WO2008043204A1

2008-04-17

CN108256562A	2018-07-06
CN103793925A	2014-05-14
CN107437246A	2017-12-05
CN107423747A	2017-12-01
CN106909924A	2017-06-30

HENSEN INTELLECTUAL PROPERTY FIRM (CN)

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