Accurate hand detection and landmark localization using the MediaPipe library. Differentiates between left and right hands, considering their orientation (front or back). Detects open and closed fingers, making it suitable for gesture recognition.

Jan 13, 2025 · The hand landmark model bundle detects the keypoint localization of 21 hand-knuckle coordinates within the detected hand regions. The model was trained on approximately 30K real-world images, as well as several rendered …

MediaPipe Hands is a high-fidelity hand and finger tracking solution. It employs machine learning (ML) to infer 21 3D landmarks of a hand from just a single frame.

Jun 3, 2023 · Discover the power of hand detection with MediaPipe and OpenCV. Build your own hand detector using Python in just Few Lines of Code and in Seconds

In this work, we present a data-driven pipeline for efficient multi-hand reconstruction in the wild. The proposed pipeline is composed of two components: a real-time fully convolutional hand localization and a high fidelity transformer-based 3D hand reconstruction model.

Hand detection and classification is a very important pre-processing step in building applications based on three-dimensional (3D) hand pose estimation and hand activity recognition.

Real-time Hand-Detection using Neural Networks (SSD) on Tensorflow. This repo documents steps and scripts used to train a hand detector using Tensorflow (Object Detection API). As with any DNN based task, the most expensive (and riskiest) part of the process has to do with finding or creating the right (annotated) dataset.

Sep 18, 2024 · In this work, we present a data-driven pipeline for efficient multi-hand reconstruction in the wild. The proposed pipeline is composed of two components: a real-time fully convolutional hand...

To detect initial hand locations, we employ a single-shot detector model called BlazePalm, optimized for mobile real-time uses in a manner similar to BlazeFace, which is also available in MediaPipe.

Jul 15, 2021 · Basically, the MediaPipe uses a single-shot palm detection model and once that is done it performs precise key point localization of 21 3D palm coordinates in the detected hand region. The MediaPipe pipeline utilizes multiple models like, a palm detection model that returns an oriented hand bounding box from the full image.