CZ-Base: A Database for Hand Gesture Recognition in Chinese Zither Intelligence EducationTraining proper hand shapes is the key to learning a musical instrument, and a timely feedback plays an important role in improving the efficiency for trainees. In this paper, we establish a comprehensive ...
The dataset used for this experimentation, “Hand gesture recognition database,” was collected from the public repository, Kaggle [20]. has 10 different folders for hand gesture images for 10 digits (0–9). Each folder has 2000 collection of images for different hand gestures for the correspon...
The recent introduction of novel acquisition devices, like the leap motion controller, allows obtaining a very informative description of the hand pose and motion that can be exploited for accurate gesture recognition. In this work, we present an interactive application with gestural hand control ...
The approach has been implemented in software and evaluated on a database of 592 gesture sequences with an overall recognition rate of 86.00\% for fully automated processing and 97.13\% for manually initialized processing. 展开 DOI: 10.1007/978-3-540-24670-1_22 ...
Hand gesture recognition database is presented, composed by a set of near infrared images acquired by the Leap Motion sensor. Content The database is composed by 10 different hand-gestures (showed above) that were performed by 10 different subjects (5 men and 5 women). The database is struc...
Explore and run machine learning code with Kaggle Notebooks | Using data from Hand Gesture Recognition Database
the hands are also discussed in this paper. Key Words: Hand Posture Detection, Hand Image Database, Gesture Recognition, Hand Posture Recognition. 1. Introduction Detecting and understanding hand and body gestures is becoming a very important and challenging task in computer vision. The significance...
In our methodologies, we first create a database (DB) of synthetic hand depth silhouettes and their corresponding hand parts-labelled maps and then train a random forests (RFs) classifier with the DB. Via the trained RFs, we recognize the hand parts in a depth silhouette. Then based on ...
To verify which of the methods presented is more accurate in case of gesture recognition, database of 2160 simple gestures was collected, and recognition procedure was implemented. The main goal was to compare the efficiency of each method assuming that each person should perform the movement ...
Since no online database of "Bharatanatyam" gestures is available to the public for research purposes, a customised database has been built with 900 images, consisting of 15 instances for each hand gesture. In this work, Chain Codes and Histogram of Oriented Gradients (HOG) are proposed for...