SimplyMime: A Control at Our Fingertips
- URL: http://arxiv.org/abs/2304.11377v1
- Date: Sat, 22 Apr 2023 11:25:19 GMT
- Title: SimplyMime: A Control at Our Fingertips
- Abstract summary: This paper presents a novel system, named SimplyMime, which aims to eliminate the need for multiple remote controls for consumer electronics.
SimplyMime leverages a dynamic hand gesture recognition architecture, incorporating Artificial Intelligence and Human-Computer Interaction.
The performance of the proposed method for detecting and recognizing gestures in a stream of motion was thoroughly tested and validated.
- Score: 0.17499351967216337
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: The utilization of consumer electronics, such as televisions, set-top boxes,
home theaters, and air conditioners, has become increasingly prevalent in
modern society as technology continues to evolve. As new devices enter our
homes each year, the accumulation of multiple infrared remote controls to
operate them not only results in a waste of energy and resources, but also
creates a cumbersome and cluttered environment for the user. This paper
presents a novel system, named SimplyMime, which aims to eliminate the need for
multiple remote controls for consumer electronics and provide the user with
intuitive control without the need for additional devices. SimplyMime leverages
a dynamic hand gesture recognition architecture, incorporating Artificial
Intelligence and Human-Computer Interaction, to create a sophisticated system
that enables users to interact with a vast majority of consumer electronics
with ease. Additionally, SimplyMime has a security aspect where it can verify
and authenticate the user utilising the palmprint, which ensures that only
authorized users can control the devices. The performance of the proposed
method for detecting and recognizing gestures in a stream of motion was
thoroughly tested and validated using multiple benchmark datasets, resulting in
commendable accuracy levels. One of the distinct advantages of the proposed
method is its minimal computational power requirements, making it highly
adaptable and reliable in a wide range of circumstances. The paper proposes
incorporating this technology into all consumer electronic devices that
currently require a secondary remote for operation, thus promoting a more
efficient and sustainable living environment.
Related papers
- An Empirical Analysis of Mobile Energy Consumption Across User Configurations [0.0]
This research aims to bridge the gap between technical energy analysis and practical user application by quantifying the energy consumption of different user-controlled parameters.<n>The objective is to have a systematic evaluation of the energy impact of user-controllable factors, including device settings.<n>By analyzing over 12,000 data points, this paper quantifies the real-world impact of common settings, revealing the trade-offs between user experience and device autonomy.
arXiv Detail & Related papers (2026-04-28T12:54:30Z) - A Minimum-Energy Control Approach for Redundant Mobile Manipulators in Physical Human-Robot Interaction Applications [0.27998963147546146]
This paper proposes a control approach for a mobile manipulator composed of a mobile base equipped with a robotic arm mounted on the top.<n>The results demonstrate that the proposed approach reduces the overall kinetic energy stored in the whole-body robotic system and improves the system performance compared with the benchmark method.
arXiv Detail & Related papers (2026-03-26T10:01:34Z) - Interpretable Multimodal Gesture Recognition for Drone and Mobile Robot Teleoperation via Log-Likelihood Ratio Fusion [14.332919759770645]
Vision-based gesture recognition has been explored as one method for hands-free teleoperation.<n>We propose a multimodal gesture recognition framework that integrates inertial data from Apple Watches on both wrists with capacitive sensing signals from custom gloves.<n>We show that our framework achieves performance comparable to a state-of-the-art vision-based baseline.
arXiv Detail & Related papers (2026-02-27T05:52:04Z) - Casper: Inferring Diverse Intents for Assistive Teleoperation with Vision Language Models [50.19518681574399]
A central challenge in real-world assistive teleoperation is for the robot to infer a wide range of human intentions from user control inputs.<n>We introduce Casper, an assistive teleoperation system that leverages commonsense knowledge embedded in pre-trained visual language models.<n>We show that Casper improves task performance, reduces human cognitive load, and achieves higher user satisfaction than direct teleoperation and assistive teleoperation baselines.
arXiv Detail & Related papers (2025-06-17T17:06:43Z) - PolyTouch: A Robust Multi-Modal Tactile Sensor for Contact-rich Manipulation Using Tactile-Diffusion Policies [4.6090500060386805]
PolyTouch is a novel robot finger that integrates camera-based tactile sensing, acoustic sensing, and peripheral visual sensing into a single design.
Experiments demonstrate a 20-fold increase in lifespan over commercial tactile sensors, with a design that is both easy to manufacture and scalable.
arXiv Detail & Related papers (2025-04-27T19:50:31Z) - Digitizing Touch with an Artificial Multimodal Fingertip [51.7029315337739]
Humans and robots both benefit from using touch to perceive and interact with the surrounding environment.
Here, we describe several conceptual and technological innovations to improve the digitization of touch.
These advances are embodied in an artificial finger-shaped sensor with advanced sensing capabilities.
arXiv Detail & Related papers (2024-11-04T18:38:50Z) - Learning Visuotactile Skills with Two Multifingered Hands [80.99370364907278]
We explore learning from human demonstrations using a bimanual system with multifingered hands and visuotactile data.
Our results mark a promising step forward in bimanual multifingered manipulation from visuotactile data.
arXiv Detail & Related papers (2024-04-25T17:59:41Z) - Agile gesture recognition for low-power applications: customisation for generalisation [41.728933551492275]
Automated hand gesture recognition has long been a focal point in the AI community.
There is an increasing demand for gesture recognition technologies that operate on low-power sensor devices.
In this study, we unveil a novel methodology for pattern recognition systems using adaptive and agile error correction.
arXiv Detail & Related papers (2024-03-12T19:34:18Z) - A Novel IoT Trust Model Leveraging Fully Distributed Behavioral
Fingerprinting and Secure Delegation [3.10770247120758]
Internet of Things (IoT) solutions are experimenting a booming demand to make data collection and processing easier.
The higher the number of new capabilities and services provided in an autonomous way, the wider the attack surface that exposes users to data hacking and lost.
In this paper, we try to provide a contribution in this setting, tackling the non-trivial issues of equipping smart things with a strategy to evaluate, also through their neighbors, the trustworthiness of an object in the network before interacting with it.
arXiv Detail & Related papers (2023-10-02T07:45:49Z) - Dynamic Hand Gesture-Featured Human Motor Adaptation in Tool Delivery
using Voice Recognition [5.13619372598999]
This paper introduces an innovative human-robot collaborative framework.
It seamlessly integrates hand gesture and dynamic movement recognition, voice recognition, and a switchable control adaptation strategy.
Experiment results have demonstrated superior performance in hand gesture recognition.
arXiv Detail & Related papers (2023-09-20T14:51:09Z) - Agile gesture recognition for capacitive sensing devices: adapting
on-the-job [55.40855017016652]
We demonstrate a hand gesture recognition system that uses signals from capacitive sensors embedded into the etee hand controller.
The controller generates real-time signals from each of the wearer five fingers.
We use a machine learning technique to analyse the time series signals and identify three features that can represent 5 fingers within 500 ms.
arXiv Detail & Related papers (2023-05-12T17:24:02Z) - Dexterous Manipulation from Images: Autonomous Real-World RL via Substep
Guidance [71.36749876465618]
We describe a system for vision-based dexterous manipulation that provides a "programming-free" approach for users to define new tasks.
Our system includes a framework for users to define a final task and intermediate sub-tasks with image examples.
experimental results with a four-finger robotic hand learning multi-stage object manipulation tasks directly in the real world.
arXiv Detail & Related papers (2022-12-19T22:50:40Z) - The Gesture Authoring Space: Authoring Customised Hand Gestures for
Grasping Virtual Objects in Immersive Virtual Environments [81.5101473684021]
This work proposes a hand gesture authoring tool for object specific grab gestures allowing virtual objects to be grabbed as in the real world.
The presented solution uses template matching for gesture recognition and requires no technical knowledge to design and create custom tailored hand gestures.
The study showed that gestures created with the proposed approach are perceived by users as a more natural input modality than the others.
arXiv Detail & Related papers (2022-07-03T18:33:33Z) - Learning, Computing, and Trustworthiness in Intelligent IoT
Environments: Performance-Energy Tradeoffs [62.91362897985057]
An Intelligent IoT Environment (iIoTe) is comprised of heterogeneous devices that can collaboratively execute semi-autonomous IoT applications.
This paper provides a state-of-the-art overview of these technologies and illustrates their functionality and performance, with special attention to the tradeoff among resources, latency, privacy and energy consumption.
arXiv Detail & Related papers (2021-10-04T19:41:42Z) - Appliance-Level Monitoring with Micro-Moment Smart Plugs [2.294014185517203]
A micro-moment-based smart plug system is proposed as part of a larger multi-appliance energy efficiency program.
The plug also allows home automation capability.
Current implementation results show that the proposed system delivers cost-effective deployment.
arXiv Detail & Related papers (2020-12-10T16:22:40Z) - DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile
Sensor with Application to In-Hand Manipulation [16.54834671357377]
General purpose in-hand manipulation remains one of the unsolved challenges of robotics.
We introduce DIGIT, an inexpensive, compact, and high-resolution tactile sensor geared towards in-hand manipulation.
arXiv Detail & Related papers (2020-05-29T17:07:54Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.