Modeling and Performance Analysis of a Notification-Based Method for Processing Video Queries on the Fly

Abstract

With the rapid growth of video data, the search for content and events in videos is becoming increasingly relevant, and many challenges arise. Various approaches have been proposed to deal with many issues. However, many open questions are still related to computational cost and latency, especially for real-time applications. Considering the need for new and efficient solutions, the so-called NOP (Notification Oriented Paradigm) could be a suitable alternative. NOP introduced a new way of thinking and developing software in which small collaborative entities perform fact execution and logical decision processing based on precise notifications. Following these concepts and practical tools, this paper proposes a new querying processing method based on NOP, focusing on search and matching in a continuous flow context. Experiments on a labeled dataset demonstrated the suitability of the proposed method for low-latency processing with polynomial complexity. The results are better than the state of the art, which works at exponential cost.