A semi-automatic approach to home video editing

Abstract

Hitchcock is a system that allows users to easily create custom videos from raw video shot with a standard video camera. In contrast to other video editing systems, Hitchcock uses automatic analysis to determine the suitability of portions of the raw video. Unsuitable video typically has fast or erratic camera motion. Hitchcock first analyzes video to identify the type and amount of camera motion: fast pan, slow zoom, etc. Based on this analysis, a numerical "unsuitability" score is computed for each frame of the video. Combined with standard editing rules, this score is used to identify clips for inclusion in the final video and to select their start and end points. To create a custom video, the user drags keyframes corresponding to the desired clips into a storyboard. Users can lengthen or shorten the clip without specifying the start and end frames explicitly. Clip lengths are balanced automatically using a spring-based algorithm.

Simplifying video editing using metadata

“…The Hitchcock system [9] automatically determines the "suitability" of the different segments in raw home video, based on camera motion, brightness, and duration. Similar clips are grouped into "piles."…”

A User-Centric System for Home Movie Summarisation

“…The Hitchcock system [10] performs automatic motion analysis of the raw video to determine which parts of the video, i.e. clips, should be included in the summary.…”

Identify Sports Video Shots with "Happy" or "Sad" Emotions

“…However, video editing remains a time-consuming and labor-intensive task because firstly, the interesting segment occurs infrequently in lengthy video documents, and secondly, good post-editing comes with skill, experience and artistic talent. For these reasons, the Automatic Video Editing problem attracts increasing research attention in recent years [1,2,3]. Intelligent video editing tools like muvee [4] are also available for both professional and amateur users.…”

“…Intelligent video editing tools like muvee [4] are also available for both professional and amateur users. However, most current video analysis techniques rely on low-level video/audio features extraction [2,3] while video editing requires high-level semantic understanding of the video content. The inability to efficiently map the low-level features to high-level semantics limits the performance of existing video editing systems.…”