Detecting a large number of objects in real-time using apache storm
Dong-Hyuck Im, Cheol-Hye Cho, IlGu Jung · 2014
Object detection is an important function for intelligent multimedia processing, but its computational complexity prevented its pervasive uses in consumer electronics. To process large-scale datasets in real-time, more resources and reliable infrastructures are required for spreading the data and running the applications across multiple machines in parallel. In order to detect a large number of objects in real-time, a task-parallel processing framework based on Storm is proposed.