Object pooling for multimedia event detection and evidence localization

Multimedia event detection (MED) and evidence hunting are two primary topics in the area of multimedia event search. The former serves to retrieve a list of relevant videos given an event query, whereas, the latter reasons why and how much the degree a retrieved video answers that query. Common practices deal with these two topics in separate methods, however, in this paper, we combine MED and evidence hunting into a joint framework. We propose a refined semantical representation named object pooling which can dynamically extract visual snippets corresponding to the location of when and where evidences might appear. The main idea of object pooling is to adaptively sample regions from frames for generation of object histogram that can be efficiently rolled up and back. Experiments conducted on large-scale TRECVID MED 2014 dataset demonstrate the effectiveness of proposed object pooling approach on both event detection and evidence hunting.