Violence Detection in Video Using Computer Vision Techniques
By E. Bermejo, Oscar Déniz-Suárez, Gloria Bueno García, Rahul Sukthankar. International Conference on Computer Analysis of Images and Patterns, 2011
527 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/25d7a9cc63fe4a6578fadd369277d45c46dfb781
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
- Jungseock Joo
- Dacheng Tao
- Tongliang Liu
- Zachary C. Steinert-Threlkeld
- Chen Gong
- Keren Fu
- Jie Yang
- Fang Shao
In Computer Vision and Pattern Recognition
- Jungseock Joo
- Tongliang Liu
- Dacheng Tao
- Sergio Escalera
- Zachary C. Steinert-Threlkeld
- Chen Gong
- Keren Fu
- Jie Yang
Citations in the corpus
- Survey on Emotional Body Gesture Recognition (2018, background): “phony [137], video conferencing and stress-monitoring tool, violence detection [138], [139], [140], video surveillance [141], and animation or synthesis of life-like agents [139] and auto-”
- Protest Activity Detection and Perceived Violence Estimation from Social Media Images (2017, background): “In addition, there have been a few works which propose to automatically classify violent activities from images or videos by static image or motion features [8, 9, 18, 33].”
- Deformed Graph Laplacian for Semisupervised Learning (2015, methodology): “As with [44], we adopted the space-time interest points and motion SIFT as action descriptors, and used the bag-of-words approach to represent each video clip as a histogram over 100 visual words.”
- Not only Look, but also Listen: Learning Multimodal Violence Detection under Weak Supervision (2020, background): “The earliest task of violence detection [25,15] can be considered as video classification.”