Investigating Effects of Users’ Background in Analyzing Long-Term Images from a Stationary Camera

• Published in: Human Interface and the Management of Information. Interaction, Visualization, and Analytics pp. 490 - 504
• Main Authors: Ikegawa, Koshi, Ishii, Akira, Okamura, Kazunori, Shizuki, Buntarou, Takahashi, Shin
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Big data management; Data visualization; Heatmap; Information presentation; Lifelog; Surveillance system; Visual analytics
• ISBN: 9783319920429; 3319920421
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-92043-6_41

Images recorded over a long term using a stationary camera have the potential for revealing various facts regarding the recorded target. We have been developing an analyzing system with a heatmap-based interface designed for visual analytics of long-term images from a stationary camera. In our previous study, we experimented with participants who were recorded in the images (recorded participants). In this study, we conducted a further experiment with participants who are not recorded in the images (unrecorded participants) to reveal the discoveries that participants obtain. By comparing the results of participants with different backgrounds, we investigated the difference between discoveries, functions used, and analysis process. The comparison suggests that unrecorded participants could discover many facts about environment, and recorded participants could discover many facts about people. Moreover, the comparison also suggests that unrecorded participants could discover many facts comparable to recorded participants.