In this project, we propose a novel semantic routing/filtering mechanism to reduce the amount of transmission loads based on the semantic user profiles. In other words, the system shall only transmit those video shots or stories that are of interest to the end users. Figure 1 shows an example of concept filtering and semantic routing for large-scale video streaming system. In the system, we deploy concept filters hierarchically based on the semantic trees. For instance, if an end user is interested at the basket clips, then the processing elements would first filter out all shots that are not sport-event, and then classify video packets to baseball, basketball, hockey, soccer, tennis, etc. Using this semantic routing structure, processing loads for each nodes can be reduced and thus make the overall system scale for large streaming environments.

We propose to use the complexity-accuracy curves to optimally choose operating points in this semantic routing scenario. We also propose a set of novel video features, that result in better performance, in terms of both speed and accuracy, than our previous generic video concept classifiers. We have built one hundred concept classification filters. Experiments on 154 hours of video streams validated the effectiveness of the proposed system.