More Like this

1. Physics Students’ Metaphorical Gestures About Energy

   https://doi.org/10.22318/icls2025.374764  

   Zhu, Minghui; Booth, Emma Teresa; Flood, Virginia J; Harrer, Benedikt W (June 2025, International Society of the Learning Sciences)

   Rajala, A; Cortez, A; Hofmann, R; Jornet, A; Lotz-Sisitka, H; Markauskaite, L (Ed.)

   Energy is a central, cross-cutting concept in science, but its abstract nature poses challenges for learners. Metaphor has been recognized as a productive resource used by students, teachers, and scientists to understand and communicate about energy. While much research has focused on metaphors about energy expressed in learners’ speech, we know less about the range of ways learners use gesture to evoke metaphors about energy. In particular, the metaphor energy as substance has been found to be useful for conceptualizing various features of energy. Using a microethnographic approach, we demonstrate how students in an introductory algebra- based university physics course use gesture in three different ways to evoke substance-like metaphors that offer valuable affordances for sensemaking about energy: These include (1) container metaphor gestures, (2) stimulus metaphor gestures, and (3) accounting metaphor gestures. Implications for learning and teaching about energy are discussed. 

   more » « less
2. Recognizing Visual Signatures of Spontaneous Head Gestures

   https://doi.org/10.1109/WACV.2018.00050  

   Sharma, Mohit; Ahmetovic, Dragan; Jeni, Laszlo A.; Kitani, Kris M. (March 2018, Winter Conference on Applications of Computer Vision)
3. UAVs Control Using 3D Hand Keypoint Gestures

   Van Khoi Nguyen and R. Alba-Flores (February 2022, SoutheastCon 2022)

   IEEE (Ed.)

   Over past few years, unmanned aircraft vehicles (UAVs) have been becoming more and more popular for various purposes such as surveillance, automated industry, robotics, vehicle guidance, traffic monitoring and control system. It is very important to have multiple methods of UAVs controlling to fit in UAVs usages. The goal of this work was to develop a new technique to control an UAV by using different hand gestures. To achieve this, a hand keypoint detection algorithm was used to detect 21 keypoints in the hand. Then this keypoints were used as the input to an intelligent system based on Convolutional Neural Networks (CNN) that was able to classify the hand gestures. To capture the hand gestures, the video camera of the UAV was used. A database containing 2400 hand images was created and used to train the CNN. The database contained 8 different hand gestures that were selected to send specific motion commands to the UAV. The accuracy of the CNN to classify the hand gestures was 93%. To test the capabilities of our intelligent control system, a small UAV, the DJI Ryze Tello drone, was used. The experimental results demonstrated that the DJI Tello drone was able to be successfully controlled by hand gestures in real time. 

   more » « less
4. Towards Surgical Context Inference and Translation to Gestures

   https://doi.org/10.1109/ICRA48891.2023.10160383  

   Hutchinson, Kay; Li, Zongyu; Reyes, Ian; Alemzadeh, Homa (May 2023, IEEE)
5. Predicting Visual Differentiability for Unmanned Aerial Vehicle Gestures

   https://doi.org/10.1109/LRA.2022.3180414  

   Fletcher, Paul; Luther, Angeline; Detweiler, Carrick; Duncan, Brittany (October 2022, IEEE Robotics and Automation Letters)