Freelance IT Specialists in RabatFreelance IT Specialists in Rabat
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EL MEHDI HICHAM's avatar
EL MEHDI HICHAM
Kenitra, Morocco
Computer Vision Engineer | Sports AI & Real-Time Video
New to Contra
Computer Vision Engineer | Sports AI & Real-Time Video
Cover image for This TactiVision demo analyses Harry
This TactiVision demo analyses Harry Kane’s penalty against Paris Saint-Germain using an automatic goal-confirmation pipeline. The system combines: goal keypoint estimation confidence-aware filtering goal-line geometry YOLO26s goal-mask segmentation ball detection and temporal tracking multi-frame goal confirmation Unlike standard object detection, the objective is not simply to detect the goal or the ball. The system must determine whether the ball crosses the reconstructed line inside the valid goal-mouth region. Kane scored the penalty in the 17th minute of Bayern’s Champions League semi-final first leg against PSG. #HarryKane (https://www.youtube.com/hashtag/harrykane) #BayernMunich (https://www.youtube.com/hashtag/bayernmunich) #PSG (https://www.youtube.com/hashtag/psg) #ChampionsLeague (https://www.youtube.com/hashtag/championsleague) #FootballAI (https://www.youtube.com/hashtag/footballai) #TactiVision (https://www.youtube.com/hashtag/tactivision)
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Cover image for Detecting a goal is easy.
Detecting a goal is easy. Knowing whether the ball actually crossed the line is a geometry problem. In this #TactiVision R&D module, I combine: goal keypoint detection to anchor the goal geometry goal segmentation to estimate the goal area confidence filtering geometric projection polygon-based validation temporal stabilization The main challenge is robustness: a single weak keypoint near the post can shift the projected goal line, so the system must decide which geometric information can be trusted before confirming a goal. This module is part of my broader football Computer Vision pipeline for detection, tracking, pitch mapping and tactical analysis
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Cover image for 7 AI Models Analyzing Football in Real-Time — This Is Footbal
7 AI Models Analyzing Football in Real-Time — This Is Footbal
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Cover image for TactiVision STEP 3 — Football
TactiVision STEP 3 — Football AI Dashboard: KPIs, Heatmaps, Pass Maps & Tactical Reports STEP_3 (https://www.linkedin.com/search/results/all/?keywords=%23step_3&origin=HASH_TAG_FROM_FEED): Data Extraction & Analytics Engine ✅ After completing detection, tracking, re-identification, and tactical mapping, the next milestone was turning the visual pipeline into a real football intelligence dashboard. STEP 3 is now focused on transforming raw match video into structured KPIs, tactical maps, live match insights, and detailed automated reports. For this demo, I tested the system on hashtag#Morocco (https://www.linkedin.com/search/results/all/?keywords=%23morocco&origin=HASH_TAG_FROM_FEED) vs hashtag#Haiti (https://www.linkedin.com/search/results/all/?keywords=%23haiti&origin=HASH_TAG_FROM_FEED) match footage, with a full tactical dashboard running around the video feed. Special mention to Fédération Royale Marocaine de Football (https://www.linkedin.com/company/f%C3%A9d%C3%A9ration-royale-marocaine-de-football/) and FIFA World Cup 2026™ - Canada, Mexico and the United States (https://www.linkedin.com/company/fifa-world-cup-2026-united-north-america-canada-usa-mexico/)— this demo is part of my ongoing work to explore how computer vision can transform football video into tactical intelligence
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IT Specialist(3)
ISMAIL HAJJY's avatar
ISMAIL HAJJY
Rabat, Morocco
Embedded Systems Expertise & Timely Delivery
Embedded Systems Expertise & Timely Delivery
Cover image for Smart Home Automation System with Raspberry Pi
Smart Home Automation System with Raspberry Pi
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Cover image for DDR3 Controller with VHDL
DDR3 Controller with VHDL
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Cover image for FOTA Project with STM32
FOTA Project with STM32
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