Shooq Alhatem

Artificial Intelligence Specialization · Cohort 2025

Contextual Understanding of Video Data for Surveillance Analysis

This project proposes a content-driven pipeline for analyzing surveillance videos by segmenting long streams into semantically meaningful, action-centered clips. Leveraging motion cues and object-level understanding, the system enables efficient indexing and retrieval of relevant events using natural-language queries, supporting intelligent surveillance analysis.

Mentor: Tanveer Hussain

Read the final report (PDF)

See it in the program report (PDF)