Will VISIONE remain competitive in lifelog image search?

Amato G., Bolettieri P., Carrara F., Falchi F., Gennaro C., Messina N., Vadicamo L., Vairo C.

Cross-modal search  Image search  Egocentric images  Lifelong image  Multimedia retrieval  Interactive system 

VISIONE is a versatile video retrieval system supporting diverse search functionalities, including free-text, similarity, and temporal searches. Its recent success in securing first place in the 2024 Video Browser Showdown (VBS) highlights its effectiveness. Originally designed for analyzing, indexing, and searching diverse video content, VISIONE can also be adapted to images from lifelog cameras thanks to its reliance on frame-based representations and retrieval mechanisms. In this paper, we present an overview of VISIONE's core characteristics and the adjustments made to accommodate lifelog images. These adjustments primarily focus on enhancing result visualization within the GUI, such as grouping images by date or hour to align with lifelog dataset imagery. It's important to note that while the GUI has been updated, the core search engine and visual content analysis components remain unchanged from the version presented at VBS 2024. Specifically, metadata such as local time, GPS coordinates, and concepts associated with images are not indexed or utilized in the system. Instead, the system relies solely on the visual content of the images, with date and time information extracted from their filenames, which are utilized exclusively within the GUI for visualization purposes. Our objective is to evaluate the system's performance within the Lifelog Search Challenge, emphasizing reliance on visual content analysis without additional metadata.

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