A Unified Multi-Faceted Video Summarization System
Anurag Sahoo, Vishal Kaushal, Khoshrav Doctor, Suyash Shetty, Rishabh, Iyer, Ganesh Ramakrishnan

TL;DR
This paper presents a unified, fast, and interactive multi-faceted video summarization system capable of generating various types of summaries, including key-frames, skims, and entity summaries, for videos, streams, and images.
Contribution
The paper introduces a scalable, explainable framework for multi-faceted video summarization that supports interactive, real-time generation of diverse summaries based on user preferences.
Findings
Summarizes hours of video data in a few seconds.
Supports interactive, customizable summaries of various types.
Demonstrates utility of different diversity, coverage, and representation models.
Abstract
This paper addresses automatic summarization and search in visual data comprising of videos, live streams and image collections in a unified manner. In particular, we propose a framework for multi-faceted summarization which extracts key-frames (image summaries), skims (video summaries) and entity summaries (summarization at the level of entities like objects, scenes, humans and faces in the video). The user can either view these as extractive summarization, or query focused summarization. Our approach first pre-processes the video or image collection once, to extract all important visual features, following which we provide an interactive mechanism to the user to summarize the video based on their choice. We investigate several diversity, coverage and representation models for all these problems, and argue the utility of these different mod- els depending on the application. While most…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsVideo Analysis and Summarization · Image Retrieval and Classification Techniques
