Network Video Frame-Skip Modeling and Simulation

被引：0
|
作者：
Cempron, Jonathan Paul C. [1 ]
Ilao, Joel P. [1 ]
机构：
[1] De La Salle Univ, Coll Comp Studies, Ctr Automat Res, Manila, Philippines
来源：
2021 27TH INTERNATIONAL CONFERENCE ON MECHATRONICS AND MACHINE VISION IN PRACTICE (M2VIP) | 2021年
关键词：
TRACKING;
D O I：
10.1109/M2VIP49856.2021.9664996
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A high video frame rate is ideal for many computer vision applications; however, this is not is usually the case for video feeds streamed from network cameras, which also exhibit frame skipping. Frame skipping can be considered as a type of degradation of the live-streamed video, and is detrimental to object tracking and other computer vision tasks. In this paper, we empirically model frame skipping and present a method for simulating frame skipping using videos with high frame rates. This simulation method was then validated by comparing the frame rate histograms of real and simulated frame-skipped videos. Finally, we demonstrate how frame skipping degrades the performance of an object tracker.
引用
收藏
页数：6
相关论文
共 50 条
  • [21] Residual Spatiotemporal Autoencoder with Skip Connected and Memory Guided Network for Detecting Video Anomalies
    S. Chandrakala
    V. Srinivas
    K. Deepak
    Neural Processing Letters, 2021, 53 : 4677 - 4692
  • [22] Multiplayer semantic Modeling of video and its semantic extraction frame
    Shi, YC
    He, X
    Zhou, XZ
    Wang, JY
    2003 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS, INTELLIGENT SYSTEMS AND SIGNAL PROCESSING, VOLS 1 AND 2, PROCEEDINGS, 2003, : 783 - 788
  • [23] Traffic modeling and simulation on a mass transit line with skip-stop policy
    Farrando, Rodolphe
    Farhi, Nadir
    Christoforou, Zoi
    Schanzenbaecher, Florian
    2020 IEEE 23RD INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2020,
  • [24] Video frame prediction of microbial growth with a recurrent neural network
    Robertson, Connor
    Wilmoth, Jared L. L.
    Retterer, Scott
    Fuentes-Cabrera, Miguel
    FRONTIERS IN MICROBIOLOGY, 2023, 13
  • [25] A Temporally-Aware Interpolation Network for Video Frame Inpainting
    Sun, Ximeng
    Szeto, Ryan
    Corso, Jason J.
    COMPUTER VISION - ACCV 2018, PT III, 2019, 11363 : 249 - 264
  • [26] Video frame interpolation using deep cascaded network structure
    Yang, Yoonmo
    Oh, Byung Tae
    SIGNAL PROCESSING-IMAGE COMMUNICATION, 2020, 89
  • [27] Flow Guidance Deformable Compensation Network for Video Frame Interpolation
    Lei, Pengcheng
    Fang, Faming
    Zeng, Tieyong
    Zhang, Guixu
    IEEE TRANSACTIONS ON MULTIMEDIA, 2024, 26 : 1801 - 1812
  • [28] A Motion Refinement Network With Local Compensation for Video Frame Interpolation
    Wang, Kaiqiao
    Liu, Peng
    IEEE ACCESS, 2023, 11 : 103092 - 103101
  • [29] Frame Augmented Alternating Attention Network for Video Question Answering
    Zhang, Wenqiao
    Tang, Siliang
    Cao, Yanpeng
    Pu, Shiliang
    Wu, Fei
    Zhuang, Yueting
    IEEE TRANSACTIONS ON MULTIMEDIA, 2020, 22 (04) : 1032 - 1041
  • [30] Inception Recurrent Neural Network Architecture for Video Frame Prediction
    Hosseini M.
    Maida A.
    Hosseini S.
    Gottumukkala R.
    SN Computer Science, 4 (1)
12345