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High-performance complex event processing framework to detect event patterns over video streams

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Piyush YadavAuthors Info & Claims

Middleware '19: Proceedings of the 20th International Middleware Conference Doctoral Symposium

Pages 47 - 50

https://doi.org/10.1145/3366624.3368169

Published: 09 December 2019 Publication History

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Abstract

Complex Event Processing (CEP) is an event processing paradigm capable of detecting patterns over streaming data in real-time. Presently, CEP systems have key challenges to preform matching over video streams due to their unstructured data model and complex video patterns which occurs over time and space. In this paper, I introduce the design, implementation and optimization of the proposed CEP framework, which enables the pattern detection over video streams. The work first proposes a Video Event Query Language (VEQL) motivated from current event query languages to write expressive video queries in CEP scenario. The query discusses how to write event query rules for video patterns and encapsulate them as high-level operators. To perform matching over VEQL queries, Video Event Knowledge Graph (VEKG) is proposed, which is a graph-based structured model of video streams. A complex event matcher is then presented which enable spatiotemporal pattern matching over videos using VEQL and VEKG constructs. Finally, three optimization strategies: state summarization, data-driven windows, and tuning deep model cascades are discussed to improve the CEP system performance which I intend to follow in my ongoing PhD research.

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Yadav, P. and Curry, E. 2019. VEKG: Video Event Knowledge Graph to Represent Video Streams for Complex Pattern Matching. IEEE Graph Computing (2019).

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Yadav, P. and Curry, E. 2019. VidCEP: Complex Event Processing Framework to Detect Spatiotemporal Patterns in Video Streams. IEEE BigData (2019).

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Yadav, P., Das, D.P. and Curry, E. 2019. Data-Driven Windows to Accelerate Video Stream Content Extraction in Complex Event Processing. ACM Middleware Poster (2019).

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Cited By

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Honarparvar SAshena ZSaeedi SLiang S(2024)A Systematic Review of Event-Matching Methods for Complex Event Detection in Video StreamsSensors10.3390/s2422723824:22(7238)Online publication date: 13-Nov-2024
https://doi.org/10.3390/s24227238
Kossoski CSimão JLopes H(2024)Modeling and Performance Analysis of a Notification-Based Method for Processing Video Queries on the FlyApplied Sciences10.3390/app1409356614:9(3566)Online publication date: 24-Apr-2024
https://doi.org/10.3390/app14093566
Yadav PSalwala DCurry E(2021)VID-WIN: Fast Video Event Matching With Query-Aware Windowing at the Edge for the Internet of Multimedia ThingsIEEE Internet of Things Journal10.1109/JIOT.2021.30753368:13(10367-10389)Online publication date: 1-Jul-2021
https://doi.org/10.1109/JIOT.2021.3075336
Show More Cited By

Index Terms

High-performance complex event processing framework to detect event patterns over video streams
1. Information systems
  1. Information systems applications
    1. Multimedia information systems
      1. Multimedia streaming
2. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Software architectures
        Publish-subscribe / event-based architectures

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Middleware '19: Proceedings of the 20th International Middleware Conference Doctoral Symposium

December 2019

59 pages

ISBN:9781450370394

DOI:10.1145/3366624

Conference Chairs:
Faisal Nawab
University of California Santa Cruz
,
Etienne Riviere
UCLouvain, Belgium

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 09 December 2019

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Middleware '19: 20th International Middleware Conference

December 9 - 13, 2019

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Overall Acceptance Rate 203 of 948 submissions, 21%

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Cited By

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Honarparvar SAshena ZSaeedi SLiang S(2024)A Systematic Review of Event-Matching Methods for Complex Event Detection in Video StreamsSensors10.3390/s2422723824:22(7238)Online publication date: 13-Nov-2024
https://doi.org/10.3390/s24227238
Kossoski CSimão JLopes H(2024)Modeling and Performance Analysis of a Notification-Based Method for Processing Video Queries on the FlyApplied Sciences10.3390/app1409356614:9(3566)Online publication date: 24-Apr-2024
https://doi.org/10.3390/app14093566
Yadav PSalwala DCurry E(2021)VID-WIN: Fast Video Event Matching With Query-Aware Windowing at the Edge for the Internet of Multimedia ThingsIEEE Internet of Things Journal10.1109/JIOT.2021.30753368:13(10367-10389)Online publication date: 1-Jul-2021
https://doi.org/10.1109/JIOT.2021.3075336
Basmi WBoulmakoul AKarim LLbath A(2021)Distributed and scalable platform architecture for smart cities complex events data collection: Covid19 pandemic use caseJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-020-02852-9Online publication date: 2-Jan-2021
https://doi.org/10.1007/s12652-020-02852-9
Yadav PSalwala DDas DCurry E(2020)Knowledge Graph Driven Approach to Represent Video Streams for Spatiotemporal Event Pattern Matching in Complex Event ProcessingInternational Journal of Semantic Computing10.1142/S1793351X2050005114:03(423-455)Online publication date: 29-Oct-2020
https://doi.org/10.1142/S1793351X20500051
Yadav PDas DCurry E(2019)Data-Driven Windows to Accelerate Video Stream Content Extraction in Complex Event ProcessingProceedings of the 20th International Middleware Conference Demos and Posters10.1145/3366627.3368115(15-16)Online publication date: 9-Dec-2019
https://dl.acm.org/doi/10.1145/3366627.3368115

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High-performance complex event processing over streams

Complex event processing over distributed probabilistic event streams

Stream reasoning and complex event processing in ETALIS

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