Deduction method of multi-video event blind area change process based on geographical semantic association constraints

Abstract

The invention relates to a deduction method for the blind area change process of multi-video events constrained by geographic semantic association, and belongs to the technical field of geographic spatial data processing, comprising the following steps: a) extracting the vertical hierarchical structure and horizontal topological network of the enhanced semantic geographic location to realize the monitoring scene interval Geographic location semantic association expression under the unified positioning and division benchmark; b) Based on the change characteristics of the relationship between trajectory and geographic location, identify the geographic movement pattern of the behavior process; c) Establish the characteristic parameters of the blind zone behavior process that maps the cost of time-space distance migration; d) Through the semantic path planning of geographic entities in monitoring blind areas combined with geographic location scenarios, geographic motion patterns, and space-time distance constraints, the blind area behavior process deduction is realized. The invention completes the geographic constraint deduction of the blind area information in the discrete change process, realizes the geographical semantic enhancement oriented to the continuous change process of the monitoring area, and supports the understanding of the complete event change process information in different levels.

Description

technical field [0001] The invention relates to a deduction method for blind area change process of multi-camera video event information constrained by geographic semantic association, and belongs to the technical field of geospatial data processing. Background technique [0002] The geographic video content acquired by a single camera is affected by the temporal and spatial locality of the imaging window, and records the short-term behavior of the characteristic object in a specific location or area. The geographic video content based on a single camera is therefore limited to parsing the corresponding local abnormal changes. Local small-scale events; although globally correlated multi-geographic videos in the network monitoring environment have effectively expanded the overall scope of the monitoring space-time window and provided geographic video datasets that record multi-scale and complex event information, the event knowledge in the data content is still limited. There...

AI Technical Summary

Problems solved by technology

Aiming at the common problem of event information blind spots in geographical video lens groups oriented to event process association clustering due to the influence of discrete distribution of monitoring equipment scope, a deduction method for the change process of multi-camera video event information blind areas with geographical semantic association constraints is proposed.

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