DEVELOPMENT OF MUSEUM VISITOR INTEREST DETECTION AND TRACKING SYSTEM BASED ON VIDEO PROCESSING IN LOW LIGHTING CONDITION
As a cultural institution, museums are responsible for protecting, developing, and utilizing their collections. To preserve their collections, museums rotate them based on visitor interest, with the expectation that more popular exhibits will attract a larger audience. Research on visitor interes...
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Format: | Theses |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/86061 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | As a cultural institution, museums are responsible for protecting, developing, and
utilizing their collections. To preserve their collections, museums rotate them based
on visitor interest, with the expectation that more popular exhibits will attract a
larger audience. Research on visitor interest is crucial to identify the most favored
collections, yet methods such as surveys and direct observation often lack accuracy
and can disrupt the visitor experience. With advancements in technology, visitor
interest analysis can be conducted using sensors, Bluetooth signals, GPS, and edge
computing. However, these methods require additional devices, which can limit
coverage in large museum areas. Moreover, low lighting in museums often poses a
challenge for accurately detecting visitor interest. This research aims to develop a
visitor interest detection and tracking system with a system architecture based on
video processing to overcome low lighting conditions. The system utilizes video
from surveillance cameras as a data source, both live and recorded, with a focus
on optimizing detection in low-light settings. To address the challenges of low
lighting, the CLAHE video enhancement technique is employed. The system is built
using a detection model developed from surveillance camera video data at the
Museum of National Awakening. The area around the museum's collections (ROI)
is used to measure visitor interest. During a one-week trial, the system successfully
detected 1,221 interested visitors and 6,666 passersby. The test results show that
the detection mode achieved an accuracy of 88.53% and an F1-score of 93.92%.
The system also improved visitor interest detection by 25% using video quality
enhancement. Usability testing indicated that 90% of 10 respondents were highly
satisfied with the system. The findings of this study have the potential to be applied
for more effective museum collection management, with recommendations for
further development and testing in various rooms and other museums. |
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