terminal://developer-profile

Vlad Voropaev

Computer Vision Engineer

I build multi-camera video analytics systems from dataset design and held-out evaluation through RTSP integration, tracking, pose logic, field iteration, and event evidence.

$ analyze rtsp --detect --track --reason
mode: developer-profile · build: industrial video analytics help · projects · research · stack · contact · matrix · clear

ready: explore the portfolio or run a command

Object detection Object tracking Pose estimation PPE & zone analytics OCR
6 camera views in a crane operator safety system
17,696 CCTV frames reviewed for a multi-camera pilot
0.920 held-out mAP@0.50 for the crane safety detector

01://INDUSTRIAL-CV

Computer Vision systems built for real operating constraints

Selected industrial Computer Vision systems developed for safety, monitoring, and multi-camera video analytics

PAID CUSTOMIZATION TYPE://SAFETY-VISION

Crane Operator Safety

A six-camera system developed end to end, from dataset design and held-out evaluation to tracking, pose logic, field debugging, and saved event evidence

  • 1,163 images and 7,499 labeled objects; YOLOv8m detector
  • 0.932 precision, 0.878 recall, 0.920 mAP@0.50, and 0.707 mAP@0.50:0.95
  • Active-view selection, ByteTrack identities, wrist-to-pendant pose association, helmet checks, and temporal voting
  • A white-helmet field failure drove targeted fine-tuning and revised weights

Python · PyTorch · Ultralytics YOLO · ByteTrack · pose estimation · event media

INDUSTRIAL PILOTS TYPE://VIDEO-ANALYTICS

RTSP Safety Analytics

Modular video analytics for PPE, danger zones, tracking and counting, equipment use, worker activity, and overlapping camera views

  • Offline PPE validation: 0.906 mAP@0.50 and 0.772 mAP@0.50:0.95 on 579 images / 1,748 objects
  • 17,696 CCTV frames reviewed from eight feeds; 1,156 relevant frames curated
  • View-specific zones reduced long-range and duplicate detections across overlapping views
  • Low-resolution worker activity used tracking, pose, fixed zones, temporal stabilization, reason labels, and event evidence

RTSP · OpenCV · detection · tracking · PPE · polygon zones · FastAPI · Docker · PostgreSQL

02://RESEARCH

NeuroQuest: video understanding to generated comic

An implemented research system with a traceable path from live video to perception, narrative, generated imagery, and PDF output

IEEE ACDSA 2024FIRST AUTHOR

Automatic generation of neurocomics based on computer vision system data

Built the end-to-end RTSP-to-comic pipeline combining detection, tracking, face and action recognition, scene interpretation, language and image generation, and PDF assembly. Led the paper writing and presented the work orally at ACDSA 2024

video perception narrative generated visuals
IEEE Xplore 10467698

03://ENGINEERING-LENS

From camera stream to evaluated system

The strongest work spans the model, the runtime logic around it, and the evidence needed to improve it in the field

A

Visual perception

Object detection, tracking, pose estimation, OCR, image preprocessing, PPE and zone analytics

B

Video intelligence

RTSP ingestion, multi-camera logic, temporal stabilization, event reasoning, evidence capture, and activity recognition

C

Evaluation and iteration

Dataset design, annotation, held-out evaluation, per-class error analysis, field failure review, and targeted retraining

D

System integration

FastAPI services, Docker, PostgreSQL-backed event flows, GPU inference, and engineering documentation

Python PyTorch OpenCV Ultralytics YOLO ByteTrack Deep SORT RTSP FastAPI Docker PostgreSQL

04://PUBLIC-CODE

Open-source engineering and earlier work

Open-source product engineering followed by selected earlier repositories

05://CONNECT

Building an industrial vision system?

For Computer Vision roles, system collaboration, or a deeper evidence walkthrough, email me or start with LinkedIn