LANDER: Visual Analysis of Activity and Uncertainty in Surveillance Video

IF 3.5 3区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

IEEE Transactions on Human-Machine Systems Pub Date : 2024-06-24 DOI:10.1109/THMS.2024.3409722

Tong Li;Guodao Sun;Baofeng Chang;Yunchao Wang;Qi Jiang;Yuanzhong Ying;Li Jiang;Haixia Wang;Ronghua Liang

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引用次数: 0

Abstract

Vision algorithms face challenges of limited visual presentation and unreliability in pedestrian activity assessment. In this article, we introduce LANDER, an interactive analysis system for visual exploration of pedestrian activity and uncertainty in surveillance videos. This visual analytics system focuses on three common categories of uncertainties in object tracking and action recognition. LANDER offers an overview visualization of activity and uncertainty, along with spatio-temporal exploration views closely associated with the scene. Expert evaluation and user study indicate that LANDER outperforms traditional video exploration in data presentation and analysis workflow. Specifically, compared to the baseline method, it excels in reducing retrieval time (

$p< $

0.01), enhancing uncertainty identification (

$p< $

0.05), and improving the user experience (

$p< $

0.05).

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LANDER：对监控视频中的活动和不确定性进行可视化分析

视觉算法在行人活动评估中面临着视觉呈现有限和不可靠的挑战。在这篇文章中，我们介绍了 LANDER--一个用于对监控视频中的行人活动和不确定性进行可视化探索的交互式分析系统。该视觉分析系统重点关注物体跟踪和动作识别中常见的三类不确定性。LANDER 提供了活动和不确定性的概览可视化，以及与场景密切相关的时空探索视图。专家评估和用户研究表明，LANDER 在数据展示和分析工作流程方面优于传统的视频探索。具体而言，与基线方法相比，它在缩短检索时间（$p< $0.01）、增强不确定性识别（$p< $0.05）和改善用户体验（$p< $0.05）方面表现出色。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Human-Machine Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS

CiteScore

7.10

自引率

11.10%

发文量

136

期刊介绍： The scope of the IEEE Transactions on Human-Machine Systems includes the fields of human machine systems. It covers human systems and human organizational interactions including cognitive ergonomics, system test and evaluation, and human information processing concerns in systems and organizations.