Name
Abstract | ||
|---|---|---|
The production and distribution of videos and animations on gaming and self-authoring websites are booming. However, given this rise in self-authoring, there is increased concern for the health and safety of people who suffer from a neurological disorder called photosensitivity or photosensitive epilepsy. These people can suffer seizures from viewing video with hazardous content. This paper presents a spatiotemporal pattern detection algorithm that can detect hazardous content in streaming video in real time. A tool is developed for producing test videos with hazardous content, and then those test videos are used to evaluate the proposed algorithm, as well as an existing post-processing tool that is currently being used for detecting such patterns. To perform the detection in real time, the proposed algorithm was implemented on a dual core processor, using a pipelined/parallel software architecture. Results indicate that the proposed method provides better detection performance, allowing for the masking of seizure inducing patterns in real time. Healthy viewing.Real-time detection of hazardous video content for photosensitive seizures.Multicore parallel computation.Seizure pattern inducer testing benchmark. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.compbiomed.2016.01.008 | Comp. in Bio. and Med. |
Keywords | Field | DocType |
Health safety,Multicore parallel processing,Pattern recognition,Photosensitivity,Photosensitive epilepsy,Real-time video streaming | Computer vision,Masking (art),Computer science,Photosensitive epilepsy,Artificial intelligence,Parallel software,Multi-core processor,Spatiotemporal pattern | Journal |
Volume | Issue | ISSN |
70 | C | 0010-4825 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohammad Alzubaidi | 1 | 2 | 3.75 |
| Mwaffaq Otoom | 2 | 38 | 6.80 |
| Abdel-Karim Tamimi | 3 | 288 | 20.26 |