Surveillance Event Detection (SED)
نویسندگان
چکیده
We report on our system used in the TRECVID 2013 Multimedia Event Detection (MED) and Multimedia Event Recounting (MER) tasks. For MED, it consists of four main steps: extracting features, representing features, training detectors and fusion. In the feature extraction part, we extract more than 10 low-level, high-level, and text features. Those features are then represented in three different ways, which are spatial bag-of-words, Gaussian Mixture Model Super Vectors (GMM) and Fisher Vectors. In the detector training and fusion, two classifiers and weighted double fusion method are employed. The official evaluation results show that our MED full systems achieve the best scores on Ah-Hoc EK10 and EK0, our audio systems achieve the best scores in EK100 and EK10 for both Pre-specified and Ad-Hoc tasks. In this report, we will analyze the contribution of each component for MED and draw some insights for video analysis. Our MER system utilizes a subset of features and detection results from the MED system from which the recounting is generated.
منابع مشابه
PKU-NEC @ TRECVid 2012 SED: Uneven-Sequence Based Event Detection in Surveillance Video
In this paper, we describe our system for interactive and retrospective surveillance event detection task in TRECVid 2012. We focus on pair-wise events (e.g., PeopleMeet, PeopleSplitUp, Embrace) that need to explore the relationship between two active persons, and action-like events (e.g. ObjectPut, CellToEar, PersonRuns and Pointing) that need to find the happenings of a person's action. Our t...
متن کاملInformedia@TRECVID 2011: Surveillance Event Detection
This paper presents a generic event detection system evaluated in the Surveillance Event Detection (SED) task of TRECVID 2011 campaign. We investigate a generic statistical approach with spatio-temporal features applied to seven event classes, which were defined by the SED task. This approach is based on local spatio-temporal descriptors, which is named as MoSIFT and generated by pair-wise vide...
متن کاملCCNY at TRECVID 2014: Surveillance Event Detection
In this paper, we present two video-based event detection systems developed by City College of New York (CCNY) for the Surveillance Event Detection (SED) task of TRECVID 2014. One is a generic event detection system that is applied to all the events of the SED task except CellToEar event. In this proposed system, the detection unit is differentiated by a sliding temporal window and a set of spa...
متن کاملINRIA-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...
متن کاملIBM-Northwestern@TRECVID 2014: Surveillance Event Detection
1 Overview We present a system for detecting events in surveillance videos and evaluate it in the SED task of TRECVID [1]. The system consists of two parts: automatic event detection (retrospective) and interactive event detection with human in the loop (interactive). The retrospective system jointly performs segmentation and classification of events in a video and applies the Sequence Memoizer...
متن کاملSJTUBCMI 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 ...
متن کامل