An Adaptive Organization Method of Geovideo Data for Spatio-Temporal Association Analysis

Abstract

ABSTRACT:Public security incidents have been increasingly challenging to address with their new features, including large-scale mobility, multistage dynamic evolution, spatio-temporal concurrency and uncertainty in the complex urban environment, which require spatiotemporal association analysis among multiple regional video data for global cognition. However, the existing video data organizational methods that view video as a property of the spatial object or position in space dissever the spatio-temporal relationship of scattered video shots captured from multiple video channels, limit the query functions on interactive retrieval between a camera and its video clips and hinder the comprehensive management of event-related scattered video shots. GeoVideo, which maps video frames onto a geographic space, is a new approach to represent the geographic world, promote security monitoring in a spatial perspective and provide a highly feasible solution to this problem. This paper analyzes the large-scale personnel mobility in public safety events and proposes a multi-level, event-related organization method with massive GeoVideo data by spatio-temporal trajectory. This paper designs a unified object identify(ID) structure to implicitly store the spatio-temporal relationship of scattered video clips and support the distributed storage management of massive cases. Finally, the validity and feasibility of this method are demonstrated through suspect tracking experiments.

Integration of Multi-Camera Video Moving Objects and GIS

“…This work mainly discussed the integration of MCVO and GIS. The implementation of the integration was carried out on the basis of V-GIS fusion [9], V-GIS practical application [1,3], and our preliminary work on single camera video object and GIS integration [10]. The advantage of this integration was that it could achieve not only the extraction of video key information and spatial correlation visualization but also the spatially associated analysis of multi-camera video object, thereby assisting users to effectively monitor video operations.…”

“…Researchers developed a series of methods for organizing V-GIS data fusion by geolocation and annotation of video data using the aforementioned models. In some of these methods (e.g., view-based R-tree [3] and camera-based topology indexing [30]), video data organization is analyzed by examining the camera field of view. The other methods used moving object texture association [31], spatial-temporal behavior association [32], and semantic association [33].…”

“…V-GIS is a geographical environment perception and analysis platform that integrates a traditional video analysis system within GIS. Under the unified geographic reference, a geospatial data service supports surveillance image intelligence analysis and realizes image-scene integrated modeling [1], video data spatialization [2], video data management analysis [3], virtual reality (VR) fusion expression [4], and other related functions. Unlike other GIS data, videos have large data volume, sparse distribution of video moving objects (like pedestrians and vehicles), and complex spatial-temporal correlation of video moving objects from different cameras.…”

Surveillance Video Synopsis in GIS

“…Surveillance cameras have spatial association with a geographic scene [4] by storing information of spatial-temporal properties within a geographic space. Although geospatial-temporal information independently exists from video images, a few sections, such as video location, camera visual field, and geospatial direction, play important roles in the effective and complete description of the video content [5]. Introducing geospatial-temporal information as key video information in the extraction and analysis of valuable we introduce related work in four aspects: video moving objects storage, fusion of GIS and video, classification of video synopsis, and optimization of video moving object expression in video synopsis.…”

Integration of GIS and Moving Objects in Surveillance Video

“…Kong et al [5] proposed a geo-video data model that can structurally process video data. Xie et al [6] proposed a hierarchical semantic model for geo-video to represent geographic video semantics. Milosavljević et al [7] implemented an efficient storage, analysis, and representation of monitoring video and geographic scene by the integration of GIS and surveillance video.…”