Partitioned Sampling, Articulated Objects, and Interface-Quality Hand Tracking

AbstractForty years ago the notion of configuration space (C-space) revolutionised robot motion planning for rigid and articulated objects. Despite great progress, handling deformable materials has remained elusive because of their infinite-dimensional shape-state space. Finding low-complexity representations has become a pressing research goal. This work tries to make a tiny step in this direction by proposing a state representation for textiles relying on the C-space of some distinctive points. A stratification of the configuration space for n points in the cloth is derived from that of the flag manifold, and topological techniques to determine adjacencies in manipulation-centred state graphs are developed. Their algorithmic implementation permits obtaining cloth state–space representations of different granularities and tailored to particular purposes. An example of their usage to distinguish between cloth states having different manipulation affordances is provided. Suggestions on how the proposed state graphs can serve as a common ground to link the perception, planning and manipulation of textiles are also made.

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

Multimedia Tools and Applications ◽

10.1007/s11042-020-10296-8 ◽

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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Annotation scaffolds for manipulating articulated objects

Autonomous Robots ◽

10.1007/s10514-021-09983-8 ◽

2021 ◽

Author(s):

Pablo Frank-Bolton ◽

Roxana Leontie ◽

Evan Drumwright ◽

Rahul Simha

Keyword(s):

Articulated Objects

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Robust hand tracking using a simple color classification technique

Proceedings of The 7th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry - VRCAI '08 ◽

10.1145/1477862.1477870 ◽

2008 ◽

Cited By ~ 4

Author(s):

Miaolong Yuan ◽

Farzam Farbiz ◽

Corey Mason Manders ◽

Ka Yin Tang

Keyword(s):

Hand Tracking ◽

Color Classification ◽

Classification Technique

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A SYSTEMATIC COLLECTION OF NATURAL INTERACTIONS FOR IMMERSIVE MODELING FROM BUILDING BLOCKS

Proceedings of the Design Society ◽

10.1017/pds.2021.29 ◽

2021 ◽

Vol 1 ◽

pp. 283-292

Author(s):

Jakob Harlan ◽

Benjamin Schleich ◽

Sandro Wartzack

Keyword(s):

User Interfaces ◽

Building Blocks ◽

Hand Tracking ◽

Spatial Concepts ◽

Natural User Interfaces ◽

Modeling Systems ◽

Block Based ◽

Natural Interactions ◽

Tracking Technology ◽

Systematic Collection

AbstractThe increased availability of affordable virtual reality hardware in the last years boosted research and development of such systems for many fields of application. While extended reality systems are well established for visualization of product data, immersive authoring tools that can create and modify that data are yet to see widespread productive use. Making use of building blocks, we see the possibility that such tools allow quick expression of spatial concepts, even for non-expert users. Optical hand-tracking technology allows the implementation of this immersive modeling using natural user interfaces. Here the users manipulated the virtual objects with their bare hands. In this work, we present a systematic collection of natural interactions suited for immersive building-block-based modeling systems. The interactions are conceptually described and categorized by the task they fulfil.

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Tomographic Proximity Imaging Using Conductive Sheet for Object Tracking

Sensors ◽

10.3390/s21082736 ◽

2021 ◽

Vol 21 (8) ◽

pp. 2736

Author(s):

Zehao Li ◽

Shunsuke Yoshimoto ◽

Akio Yamamoto

Keyword(s):

Inverse Problem ◽

Theoretical Model ◽

Low Cost ◽

Hand Tracking ◽

Depth Camera ◽

Capacitance Density ◽

Evaluation Test ◽

Density Problem ◽

Imaging Sensor ◽

Tomographic Approach

This paper proposes a proximity imaging sensor based on a tomographic approach with a low-cost conductive sheet. Particularly, by defining capacitance density, physical proximity information is transformed into electric potential. A novel theoretical model is developed to solve the capacitance density problem using the tomographic approach. Additionally, a prototype is built and tested based on the model, and the system solves an inverse problem for imaging the capacitance density change that indicates the object’s proximity change. In the evaluation test, the prototype reaches an error rate of 10.0–15.8% in horizontal localization at different heights. Finally, a hand-tracking demonstration is carried out, where a position difference of 33.8–46.7 mm between the proposed sensor and depth camera is achieved at 30 fps.

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