Piyush Yadav
Gradientor Podcast
Podcast Episode- VidCEP: Complex Event Processing Framework to Detect Spatiotemporal Patterns in Video Streams
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Podcast Episode- VidCEP: Complex Event Processing Framework to Detect Spatiotemporal Patterns in Video Streams

AI Generated Podcast

This one of the paper authored by me. I thought it would be great idea to listen this in a podcast style for general audience. So here it is- an AI generated podcast episode for the paper.

Abstract

The paper introduces VidCEP, a novel Complex Event Processing (CEP) framework designed for analysing video streams to detect spatiotemporal patterns. It addresses limitations in current CEP systems by using a graph-based representation of video data named Video Event Knowledge Graph (VEKG). VidCEP enables users to formulate expressive queries using a new Video Event Query Language (VEQL), facilitating the detection of events like object recognition and traffic flow monitoring. The framework then matches these queries against video content in near real-time, with demonstrated performance achieving a throughput of 70 frames per second. The system aims to bridge the gap between low-level video data and high-level semantic understanding, enabling more sophisticated video analytics. The research also evaluates the framework's performance with experiments that measure event representation time, accuracy, latency and overall throughput.

Reference

  1. Yadav, Piyush, and Edward Curry. "Vidcep: Complex event processing framework to detect spatiotemporal patterns in video streams." In 2019 IEEE International conference on big data (big data), pp. 2513-2522. IEEE, 2019.

  2. Google Gemini, NotebookLM

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