kccistc/intel-08
Sep 2025 – Sep 2025
1 Month active
Languages Used
MarkdownPython
Technical Skills
Action RecognitionComputer VisionDeep LearningDocumentationObject DetectionPose Estimation
Chanmi Kim
PROFILE
Chanmi Kim
During their work on the kccistc/intel-08 repository, Channeunim developed an end-to-end Fall Detection System designed for real-time safety monitoring. They integrated YOLO for person detection, SPPE for pose estimation, and ST-GCN for action recognition, creating a pipeline that identifies individuals, estimates their poses, and classifies actions to detect falls. The implementation leveraged Python and PyTorch, applying deep learning and computer vision techniques to address a safety-critical problem. In addition to engineering the detection system, Channeunim updated project documentation in Markdown to reflect team changes. The work demonstrated focused technical depth within a concise development period.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
5,524
Activity Months1
Your Network
27 people
Work History
September 2025
2 Commits • 2 Features
Sep 1, 20252025-09 monthly summary for kccistc/intel-08. Delivered the Fall Detection System by integrating YOLO for person detection, SPPE for pose estimation, and ST-GCN for action recognition to detect falls. This end-to-end pipeline establishes components to detect individuals, estimate poses, and classify actions, enabling real-time fall detection in safety-critical contexts. Also updated project documentation to reflect team changes by adding a new member to README. Key commits are listed below for traceability.
2 Commits • 2 Features
Sep 1, 20252025-09 monthly summary for kccistc/intel-08. Delivered the Fall Detection System by integrating YOLO for person detection, SPPE for pose estimation, and ST-GCN for action recognition to detect falls. This end-to-end pipeline establishes components to detect individuals, estimate poses, and classify actions, enabling real-time fall detection in safety-critical contexts. Also updated project documentation to reflect team changes by adding a new member to README. Key commits are listed below for traceability.
September 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture100.0%
Performance90.0%
AI Usage50.0%
Skills & Technologies
Programming Languages
MarkdownPython
Technical Skills
Action RecognitionComputer VisionDeep LearningDocumentationObject DetectionPose EstimationPyTorch
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