TY - GEN
T1 - Video saliency detection using the propagation of image saliency between frames
AU - Zhu, Shaotong
AU - Zhang, Yingtao
AU - Liang, Tian
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - Recently, the saliency detection of image and video has attracted more and more attention due to its wide application. In this paper, we propose an image registration method based on SLIC image segmentation algorithm, which is used to realize the saliency information propagate between frame and frame. First, we use SLIC algorithm to divide each image in video into many regions, obtain the brightness and color information of each frame through LAB color space. Then, use the optical flow method to get the motion information of each frame. At the same time, the saliency information of the first frame is calculated by the method of Li et al [1]. Then, the following procedure is iterated from the first frame: First of all, we perform the registration with the divided regions as processing units, after that, saliency map of this frame is weighted according to the criterion of motion and color and brightness changes, and the result becomes saliency information of the next frame. The salience information obtained by each iteration is generated as a new frame, and the salience result of the video is obtained. The proposed method has been tested in two sets of video sequences and obtained good results.
AB - Recently, the saliency detection of image and video has attracted more and more attention due to its wide application. In this paper, we propose an image registration method based on SLIC image segmentation algorithm, which is used to realize the saliency information propagate between frame and frame. First, we use SLIC algorithm to divide each image in video into many regions, obtain the brightness and color information of each frame through LAB color space. Then, use the optical flow method to get the motion information of each frame. At the same time, the saliency information of the first frame is calculated by the method of Li et al [1]. Then, the following procedure is iterated from the first frame: First of all, we perform the registration with the divided regions as processing units, after that, saliency map of this frame is weighted according to the criterion of motion and color and brightness changes, and the result becomes saliency information of the next frame. The salience information obtained by each iteration is generated as a new frame, and the salience result of the video is obtained. The proposed method has been tested in two sets of video sequences and obtained good results.
KW - SLIC
KW - color histogram
KW - optical flow
KW - video saliency
UR - https://www.scopus.com/pages/publications/85046692680
U2 - 10.1109/ITNEC.2017.8284774
DO - 10.1109/ITNEC.2017.8284774
M3 - 会议稿件
AN - SCOPUS:85046692680
T3 - Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017
SP - 459
EP - 467
BT - Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017
A2 - Xu, Bing
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017
Y2 - 15 December 2017 through 17 December 2017
ER -