Footage Analysis Toolkit: A System for Semantic Video Retrieval and Structured Forensic Analysis

Abstract

The massive growth of digital video repositories in surveillance, media and corporate domains is producing significant challenges for scalable indexing and retrieval and structured analysis of video content. Manual review and coarse filtering using metadata are both ineffective for very large forensic archives and do not have the ability to capture the semantically rich content contained in video images. This paper provides an overview of the Footage Analysis Toolkit (FAT) which is a modular, integrated platform for forensic oriented processing and semantic video retrieval and is based on a unified system architecture. FAT allows for content based search by providing a common semantic representation that maps video imagery to natural language search requests and also includes methods for extracting structured metadata and aligning timestamps for precise navigation across modules and ensuring cross-module consistency. In addition, FAT has been designed to allow for modular integration of additional tools, controlled management
of indexes and non-destructive manipulation of original video content to provide a record of all analysis performed. Collectively,
FAT forms a systematic and extensible foundation for the development of semantic video retrieval and structured video analysis systems in forensic environments.