Object-based on-line video summarization for internet of video things

In order to address the high transmission bandwidth requirement of an Internet-of-Video-Things (IoVT), an object-based on-line video summarization algorithm is proposed to summarize the captured video information at the sensor nodes before being transmitted to the server. It is composed of two stages: intra-view and inter-view stages. In the intra-view stage, human object detector is employed with the proposed human object descriptor. In the inter-view stage, an on-line clustering algorithm with a two-layer K-nearest-neighbor model is also proposed for object clustering. Experimental results show that significant improvement can be achieved when compared with state-of-the-art works.