Quantifying the amount of spatial and temporal information in video test sequences

被引：23

作者：

Ostaszewska, A. ^{[1
]}

Kloda, R. ^{[1
]}

机构：

[1] Warsaw Univ Technol, Fac Mechatron, Sw Andrzeja Boboli 8 Str, PL-02525 Warsaw, Poland

来源：

RECENT ADVANCES IN MECHATRONICS | 2007年

关键词：

D O I：

10.1007/978-3-540-73956-2_3

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In case of compressed video quality assessment, the selection of test scenes is an important issue. So far there was only one conception for evaluation the level of scene complication. It was given in International Telecommunication Union recommendations and was broadly used. Authors investigated features of recommended parameters. The paper presents the incompatibility of those parameters with human perception that was discovered and gives a proposal of modification in algorithm, which improves accordance of parameters with observers' opinion.

引用

页码：11 / +

页数：2

共 50 条

[41] A spatial-frequency-temporal domain based saliency model for low contrast video sequences
Mu, Nan
Xu, Xin
Zhang, Xiaolong
[J]. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2019, 58 : 79 - 88
[42] Accurate Object Segmentation for Video Sequences via Temporal-Spatial-Frequency Saliency Model
Xu, Bing
Niu, Yanxiong
[J]. IEEE INTELLIGENT SYSTEMS, 2018, 33 (01) : 18 - 28
[43] Concurrent learning of temporal and spatial sequences
Shin, JC
Ivry, RB
[J]. JOURNAL OF EXPERIMENTAL PSYCHOLOGY-LEARNING MEMORY AND COGNITION, 2002, 28 (03) : 445 - 457
[44] Quantifying spatial and temporal variability of macroinvertebrate metrics
Keizer-Vlek, Hanneke E.
Verdonschot, Piet F. M.
Verdonschot, Ralf C. M.
Goedhart, Paul W.
[J]. ECOLOGICAL INDICATORS, 2012, 23 : 384 - 393
[45] Quantifying the Amount of Visual Information Used by Neural Caption Generators
Tanti, Marc
Gatt, Albert
Camilleri, Kenneth P.
[J]. COMPUTER VISION - ECCV 2018 WORKSHOPS, PT IV, 2019, 11132 : 124 - 132
[46] Using fuzzy information granulation for spatio-temporal salient unit detection in video sequences
Lang, Cong-Yan
Xu, De
Li, Bing
[J]. Tien Tzu Hsueh Pao/Acta Electronica Sinica, 2007, 35 (10): : 2023 - 2028
[47] Moving Object Detection in Video Sequences Based on a Two-Frame Temporal Information CNN
Chacon-Murguia, Mario I.
Guzman-Pando, Abimael
[J]. NEURAL PROCESSING LETTERS, 2023, 55 (05) : 5425 - 5449
[48] Moving Object Detection in Video Sequences Based on a Two-Frame Temporal Information CNN
Mario I. Chacon-Murguia
Abimael Guzman-Pando
[J]. Neural Processing Letters, 2023, 55 : 5425 - 5449
[49] Finding the optimal temporal partitioning of video sequences
Truong, BT
Venkatesh, S
[J]. 2005 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO (ICME), VOLS 1 AND 2, 2005, : 1183 - 1186
[50] Temporal Segmentation of Facial Expressions in Video Sequences
Xue, Yu
Mei, Xue
Bian, Jiali
Wu, Liang
Ding, Yao
[J]. PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017), 2017, : 10789 - 10794

← 1 2 3 4 5 →