Lin, S.-T.S.-T.LinLiao, Y.-H.Y.-H.LiaoTsao, Y.Y.TsaoSHAO-YI CHIEN2020-06-162020-06-16201702714310https://scholars.lib.ntu.edu.tw/handle/123456789/502340In 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. © 2017 IEEE.Nearest neighbor search; Object detection; Sensor nodes; Video recording; High transmission; K-nearest neighbors; Object based; Object clustering; Object detectors; State of the art; Video information; Video summarization; Clustering algorithmsconference paper10.1109/ISCAS.2017.80502372-s2.0-85032698093