Recognition of Human Actions from RGB-D Videos Using a Reject Option

By Vincenzo Carletti, Pasquale Foggia, Gennaro Percannella, Alessia Saggese, Mario Vento. 2013

28 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition

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

1. Mario Vento
2. Alessia Saggese
3. Luc Brun
4. Pasquale Foggia
5. Nicola Strisciuglio
6. Horst Bunke
7. Kaspar Riesen

In Computer Vision and Pattern Recognition

1. Mario Vento
2. Alessia Saggese
3. Luc Brun
4. Pasquale Foggia
5. Gennaro Percannella
6. Nicola Strisciuglio
7. Horst Bunke
8. Kaspar Riesen

Citations in the corpus

• Recognition of Human Actions using Edit Distance on Aclet Strings (2015, background): “…(Ofli et al., 2012) 82.2 BM2 (Cheema et al., 2013) 87.8 (b) Method Source Accuracy HARED Proposed 85.2 Cuboids (Dollar et al., 2005) 74.4 Reject (Carletti et al., 2013) 79.8 Bow (Foggia et al., 2013) 84.1 HAcK (Brun et al., 2014) 80.1 Deep (Foggia et al., 2014) 84.7 both the datasets the…”
• HAck: A system for the recognition of human actions by kernels of visual strings (2014, methodology): “Starting from the so obtained images, a first-level feature vector is extracted by taking advantage on the combination recently exploited in [3] and [7].”
• Exploiting the deep learning paradigm for recognizing human actions (2014, background): “The results obtained by the proposed approach (Prop in the tables) are compared with [10], [7] and [9].”