Trajectory Retrieval System Using Spatial Indexing
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Solution Overview
Problem
Surveillance systems face inefficiencies in searching large amounts of video data for trajectory information of moving objects, as existing methods are slow and require significant manual effort to retrieve relevant data from recorded video sequences.
Innovation Solution
A trajectory data retrieval system that uses a database to store common routes generated from multiple trajectories, employing a path learning algorithm to match query trajectories with stored data, and includes querying means to formulate and process trajectory-based queries, allowing for intuitive search queries and efficient retrieval of matching data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional video data search methods are used to retrieve trajectory information, then complete trajectory data can be obtained, but the search speed is slow and processing time is long
Solution Approach 1:
The system pre-processes video data to extract and store trajectory information in a structured database before actual search operations. Trajectories are segmented into key points and stored with spatial indexes, so that during retrieval, the system only needs to query pre-processed data rather than analyzing raw video streams in real-time.
Solution Approach 2:
The patent replaces manual or conventional sequential video scanning with automated database querying mechanisms. Spatial indexes and trajectory databases substitute for frame-by-frame video analysis, enabling rapid retrieval through structured data access rather than mechanical video playback and analysis.
2Productivity
If manual methods are used to search through recorded video sequences for trajectory data, then accurate trajectory information can be extracted, but significant manual effort is required
Solution Approach 1:
The system automatically performs trajectory extraction, segmentation, and database indexing without requiring manual intervention. The trajectory database is self-populated through automated video analysis algorithms that extract moving object trajectories and store them in structured formats with spatial indexes.
Solution Approach 2:
The patent extracts only the essential trajectory information (key points, spatial coordinates, temporal data) from complete video sequences and stores them separately in a trajectory database. This extraction separates critical search data from the full video content, enabling rapid querying without handling entire video files.
3Reliability
If a database stores detailed trajectory information from multiple trajectories, then comprehensive trajectory data is available, but the database complexity increases
Solution Approach 1:
The patent segments trajectories into discrete key points or significant events rather than storing continuous trajectory data. Each trajectory is represented by a sequence of key points with spatial and temporal attributes, making the data more manageable and queryable while retaining essential movement information.
Solution Approach 2:
The system adds spatial indexing dimensions to the trajectory database, organizing data not just by temporal sequence but also by spatial location. This multi-dimensional organization allows queries to leverage both temporal and spatial indexes, improving retrieval efficiency while managing data complexity through structured multidimensional storage.
Data Source
AI summary
Surveillance systems are used in general to monitor buildings, public places, traffic and the like. These systems conventionally comprise a plurality of surveillance cameras producing a large amount of video data. The video data is viewed on-line or recorded and searched through off-line. Especially in the latter case there is a strong need to improve the search speed due to the large amount of the video data. A trajectory data retrieval system 1 for retrieving trajectory data of moving objects in a plurality of image sequences is proposed, the trajectory data retrieval system 1 comprising a database 4 realized for storing a set of common routes based on the trajectories of the moving objects, whereby each subset of the set of common routes is generated by a plurality of trajectories and whereby each subset is linked with the trajectory data of its generating trajectories and/or parts thereof and/or of trajectories overlapping at least in part with the subset, querying means 7 realized to formulate a trajectory-based query and retrieval means 8 realized to retrieve trajectory data linked to a matching subset of the set of common routes matching with the trajectory-based query.