Depth-Based Real-Time Hand Tracking with Occlusion Handling Using Kalman Filter and DAM-Shift

2015 ◽  
pp. 218-226 ◽  
Author(s):  
Kisang Kim ◽  
Hyung-Il Choi
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Hand Tracking ◽  
Occlusion Handling

Adaptive Kalman Filter Incorporated Eigenhand (AKFIE) for real-time hand tracking system

2014 ◽  
Vol 74 (21) ◽  
pp. 9231-9257 ◽  
Author(s):  
Mohd Shahrimie Mohd Asaari ◽  
Bakhtiar Affendi Rosdi ◽  
Shahrel Azmin Suandi
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Tracking System ◽  
Hand Tracking ◽  
Adaptive Kalman Filter

Real-time Hand Tracking using the RGB-D Camera

2017 ◽  
Vol 8 (2) ◽  
pp. 13-20 ◽  
Author(s):  
Seok-Han Lee ◽  
Keyword(s):  
Real Time ◽  
Hand Tracking

scholarly journals Data integration by two-sensors in a LEAP-based Virtual Glove for human-system interaction

2021 ◽  
Author(s):  
Giuseppe Placidi ◽  
Danilo Avola ◽  
Luigi Cinque ◽  
Matteo Polsinelli ◽  
Eleni Theodoridou ◽  
...  
Keyword(s):  
Data Integration ◽  
Real Time ◽  
Vision System ◽  
Hand Tracking ◽  
Selection Strategy ◽  
Motion Sensors ◽  
Leap Motion ◽  
Time Data ◽  
Lower Velocity ◽  
Human System

AbstractVirtual Glove (VG) is a low-cost computer vision system that utilizes two orthogonal LEAP motion sensors to provide detailed 4D hand tracking in real–time. VG can find many applications in the field of human-system interaction, such as remote control of machines or tele-rehabilitation. An innovative and efficient data-integration strategy, based on the velocity calculation, for selecting data from one of the LEAPs at each time, is proposed for VG. The position of each joint of the hand model, when obscured to a LEAP, is guessed and tends to flicker. Since VG uses two LEAP sensors, two spatial representations are available each moment for each joint: the method consists of the selection of the one with the lower velocity at each time instant. Choosing the smoother trajectory leads to VG stabilization and precision optimization, reduces occlusions (parts of the hand or handling objects obscuring other hand parts) and/or, when both sensors are seeing the same joint, reduces the number of outliers produced by hardware instabilities. The strategy is experimentally evaluated, in terms of reduction of outliers with respect to a previously used data selection strategy on VG, and results are reported and discussed. In the future, an objective test set has to be imagined, designed, and realized, also with the help of an external precise positioning equipment, to allow also quantitative and objective evaluation of the gain in precision and, maybe, of the intrinsic limitations of the proposed strategy. Moreover, advanced Artificial Intelligence-based (AI-based) real-time data integration strategies, specific for VG, will be designed and tested on the resulting dataset.

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