mlsanityData to 14 Oct 2026

Scene Separation & Data Selection: Temporal Segmentation Algorithm for Real-Time Video Stream Analysis

arXiv 2308.00210 ↗First posted 1 Aug 2023cs.CVcited by 0

Not on the map. Why?

Abstract (arXiv)

We present 2SDS (Scene Separation and Data Selection algorithm), a temporal segmentation algorithm used in real-time video stream interpretation. It complements CNN-based models to make use of temporal information in videos. 2SDS can detect the change between scenes in a video stream by com-paring the image difference between two frames. It separates a video into segments (scenes), and by combining itself with a CNN model, 2SDS can select the optimal result for each scene. In this paper, we will be discussing some basic methods and concepts behind 2SDS, as well as presenting some preliminary experiment results regarding 2SDS. During these experiments, 2SDS has achieved an overall accuracy of over 90%.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 11 references that are in the map. First posted on arXiv 1 Aug 2023.

Builds on

5 of 11 references.

References · 5

  1. 2018SlowFast Networks for Video Recognitioncited by 1,867
  2. 2018YouTube-VOS: A Large-Scale Video Object Segmentation Benchmarkcited by 383
  3. 2021Multiscale Spatio-Temporal Graph Neural Networks for 3D Skeleton-Based Motion Predictioncited by 37
  4. 2017Temporal 3D ConvNets: New Architecture and Transfer Learning for Video Classificationcited by 27
  5. 2019Comparative Analysis of CNN-based Spatiotemporal Reasoning in Videoscited by 2

Built on by

Not cited yet.