Audio-visual classification and detection of human manipulation actions
By Alessandro Pieropan, Giampiero Salvi, Karl Pauwels, Hedvig Kjellström. 2014
58 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Human-Computer Interaction
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- German Ignacio Parisi
- Stefan Wermter
- Luiza Mici
- Vassilis Athitsos
- Isabelle M Guyon
- Sergio Escalera
- Cornelius Weber
- Vincenzo Lomonaco
In Computer Vision and Pattern Recognition
- German Ignacio Parisi
- Stefan Wermter
- Luiza Mici
- Sergio Escalera
- Isabelle M Guyon
- Vassilis Athitsos
- Cornelius Weber
- Liang Wang
In Human-Computer Interaction
- Stefan Wermter
- German Ignacio Parisi
- Luiza Mici
- Sergio Escalera
- Isabelle M Guyon
- Vassilis Athitsos
- Liang Wang
- Jun Wan
Citations in the corpus
- A self-organizing neural network architecture for learning human-object interactions (2017, background): “[33] proposed including action-related audio cues in addition to the spatial relation among objects in order to learn object manipulations for the purpose of robot learning by imitation.”
- Depth-Based Hand Pose Estimation: Methods, Data, and Challenges (2015, unknown): “However, because of difficulties in manual annotation (a point that we will revisit), evaluation was not always quantitative - instead, it has been common to show select frames to give a qualitative sense of performance [5,21].”
- Challenges in multimodal gesture recognition (2016, background): “For such settings, one approach for achieving context awareness is scene analysis, where information is extracted from the scene around the subject (e.g., Pieropan et al. (2014); Shapovalova et al. (2011)).”