Toshiba at TRECVID 2008: Surveillance Event Detection Task

University of Central Florida at TRECVID 2008 Content Based Copy Detection and Surveillance Event Detection

In this paper, we describe our approaches and experiments in content-based copy detection (CBCD) and surveillance event detection pilot (SEDP) tasks of TRECVID 2008. We have participated in the video-only CBCD task and four of the SEDP events. The CBCD method relies on sequences of invariant global image features and efficiently matching and ranking of those sequences. The normalized Hu-moments...

SJTUBCMI at TRECVID 2012: Surveillance Event Detection

In TRECVID 2012, our team takes part in the Surveillance Event Detection (SED) task and has finished four human events detection. We investigate an unsupervised learning approach based on an extended Independent Subspace Analysis model to extract spatio-temporal feature directly from the video data. The bag-of-words procedure and SVM classifier is used. We present the results and comparison of ...

Event analysis on TRECVid 2008 LondonGatwick dataset

In this paper we perform event analysis on a challenging surveillance dataset without any artificial events. We analyze low-level and high-level features such as motion vectors, change detection and pedestrian detections for recognition of events. We performed detection of three events namely person runs, elevator no entry and opposing flow. The event detection is performed on 60 hours of TRECV...

NHK STRL at TRECVID 2008: High-Level Feature Extraction and Surveillance Event Detection

INRIA-WILLOW at TRECVID 2010 : Surveillance Event Detection

This notebook paper presents a system evaluated in the Surveillance Event Detection (SED) task of TRECVid 2010 campaign. We investigate a generic statistical approach applied to seven event classes defined by the SED task. Our video representation is based on local space-time descriptors which are vectorquantized and aggregated into histograms within short temporal windows and spatial regions d...