most citedVidCEP: Complex Event Processing Framework to Detect Spatiotemporal Patterns in Video Streams

33 citations · 69 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2021★ 26 cited

VID-WIN: Fast Video Event Matching with Query-Aware Windowing at the Edge for the Internet of Multimedia Things

Piyush Yadav, Dhaval Salwala, Edward Curry

Efficient video processing is a critical component in many IoMT applications to detect events of interest. Presently, many window optimization techniques have been proposed in even…

cs.SI2021★ 1 cited

Donut visualizations for network-level and regional-level overview of Spatial Social Networks

Dipto Sarkar, Piyush Yadav

Spatial Social Networks (SSN) build on the node and edge structure used in Social Network Analysis (SNA) by incorporating spatial information. Thus, SSNs include both topological a…

cs.CL2020

MuSeM: Detecting Incongruent News Headlines using Mutual Attentive Semantic Matching

Rahul Mishra, Piyush Yadav, Remi Calizzano +1

Measuring the congruence between two texts has several useful applications, such as detecting the prevalent deceptive and misleading news headlines on the web. Many works have prop…

cs.AI2020

Visual Semantic Multimedia Event Model for Complex Event Detection in Video Streams

Piyush Yadav, Edward Curry

Multimedia data is highly expressive and has traditionally been very difficult for a machine to interpret. Middleware systems such as complex event processing (CEP) mine patterns f…

cs.CV2020★ 33 cited

VidCEP: Complex Event Processing Framework to Detect Spatiotemporal Patterns in Video Streams

Piyush Yadav, Edward Curry

Video data is highly expressive and has traditionally been very difficult for a machine to interpret. Querying event patterns from video streams is challenging due to its unstructu…

cs.CV2020

Knowledge Graph Driven Approach to Represent Video Streams for Spatiotemporal Event Pattern Matching in Complex Event Processing

Piyush Yadav, Dhaval Salwala, Edward Curry

Complex Event Processing (CEP) is an event processing paradigm to perform real-time analytics over streaming data and match high-level event patterns. Presently, CEP is limited to…