VideoPro: A Visual Analytics Approach for Interactive Video Programming

TL;DR

VideoPro is a visual analytics system that simplifies and accelerates the creation of labeled video data for machine learning by extracting events, mining templates, and supporting iterative model improvement.

Contribution

It introduces a novel visual analytics approach combining event extraction, template mining, and interactive exploration to facilitate scalable video data programming with reduced human effort.

Findings

Effective in reducing manual labeling effort

Supports scalable and flexible video data programming

Demonstrated success in case studies and expert evaluations

Abstract

Constructing supervised machine learning models for real-world video analysis require substantial labeled data, which is costly to acquire due to scarce domain expertise and laborious manual inspection. While data programming shows promise in generating labeled data at scale with user-defined labeling functions, the high dimensional and complex temporal information in videos poses additional challenges for effectively composing and evaluating labeling functions. In this paper, we propose VideoPro, a visual analytics approach to support flexible and scalable video data programming for model steering with reduced human effort. We first extract human-understandable events from videos using computer vision techniques and treat them as atomic components of labeling functions. We further propose a two-stage template mining algorithm that characterizes the sequential patterns of these events to serve as labeling function templates for efficient data labeling. The visual interface of VideoPro facilitates multifaceted exploration, examination, and application of the labeling templates, allowing for effective programming of video data at scale. Moreover, users can monitor the impact of programming on model performance and make informed adjustments during the iterative programming process. We demonstrate the efficiency and effectiveness of our approach with two case studies and expert interviews.