sujalmh / AI-Powered-Surveillance-System-with-Natural-Language-based-Querying
This project transforms passive CCTV video streams into a searchable, proactive intelligence asset. It integrates computer vision, deep learning, and Natural Language Processing (NLP) to enable real-time monitoring, crowd density estimation, and forensic video retrieval using conversational queries.
Leaderboard
4 collaborators · ranked by impactEvery collaborator as a stat card — Impact, Quality, Collab, Consistency and a Total score.
Team Health
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Stat tiles + AI work summarysujalmh
Tier · BuilderAuthored and merged multiple feature PRs that advanced both frontend and backend of the AI-powered surveillance system, including enhanced chat/retrieval processing, a video indexing…
sujnankumar
Tier · BuilderFocused on delivering backend features and fixes for the surveillance system, implementing natural language chat APIs, object detection enhancements, and video processing improvements. Also…
Yashas-Shetty
Tier · BuilderImplemented and merged core feature work for the surveillance system, including LLM-based natural language query parsing and zone management for crowd detection, spanning both…
Suhan-D-Shet
Tier · BuilderDelivered the alert engine setup feature which was merged, and contributed an Intel OpenVINO person attribute recognition module, focusing on backend and frontend feature…
Work Areas Treemap
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AI Insights
Per-person findingsThe repository saw a burst of development focused on strengthening natural language querying, video retrieval and clip generation, streaming reliability, and detection accuracy. Two contributors shipped a series of PRs adding chat/NLP capabilities, unified retrieval pipelines, and backend robustness improvements.
Object detection, tracking, and attribute recognition pushes were all authored by sujnankumar.
Video clip generation and MP4 timing correction changes were exclusively pushed by sujnankumar.
Color accuracy and CIEDE2000 color matching work was exclusively pushed by sujnankumar.
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