Interactive Object Retrieval via Time-Space Filtering
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Solution Overview
Problem
Current surveillance camera networks face challenges in accurate automated analysis due to varying camera resolutions and light conditions, leading to time-consuming data processing and inefficient search results, especially when trying to track objects across multiple cameras.
Innovation Solution
An interactive object retrieval method and system that uses a filtering module and an interactive module to select and display search results based on time-space conditions, user feedback, and similarity analysis, allowing for dynamic adjustment of search results and improved user interface interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automated analysis algorithms are used to process surveillance video data, then object detection and classification can be performed, but processing time increases significantly due to the huge amount of data from multiple cameras with different resolutions and lighting conditions
Solution Approach 1:
The patent segments the video data processing by dividing it into multiple categories (e.g., pedestrian, vehicle, animal) and processes each category separately using category-specific algorithms. This segmentation allows the system to focus computational resources on relevant objects rather than processing all video data uniformly, thereby reducing overall processing time while maintaining detection accuracy.
Solution Approach 2:
The patent implements preliminary filtering and preprocessing steps before full automated analysis. The system first performs basic video content analysis to identify potential objects of interest, then applies more sophisticated algorithms only to these pre-selected segments. This preliminary action reduces the volume of data requiring intensive processing, thus decreasing processing time while preserving detection precision.
2Reliability
If cross-camera object association is implemented to track objects across multiple cameras, then object tracking capability is improved, but the complexity of data processing and result verification increases
Solution Approach 1:
The patent incorporates feedback mechanisms where the system continuously monitors tracking results and adjusts its processing accordingly. When objects are successfully tracked across cameras, the system learns from these successful associations and applies similar patterns to future tracking tasks. This feedback loop improves tracking reliability while reducing the need for complex manual verification by making the system progressively more accurate.
Solution Approach 2:
The patent introduces an intermediary layer that standardizes data from multiple cameras with different resolutions and formats before performing cross-camera association. This intermediary processing layer normalizes the input data, making it easier to match objects across different camera views without requiring complex pairwise comparisons, thus reducing processing complexity while maintaining tracking accuracy.
3Measurement precision
If strict filtering conditions are applied to select search results from the object database, then search accuracy is improved, but the number of valid search results decreases
Solution Approach 1:
The patent implements dynamic filtering where the strictness of filtering conditions can be adjusted based on the search context and user needs. The system starts with moderate filtering to obtain a reasonable number of results, then applies additional filters iteratively based on user feedback or result quality assessment. This dynamic approach allows the system to maintain a balance between result quantity and accuracy, adapting the filtering level to the specific search scenario.
Data Source
AI summary
An interactive object retrieval method is provided. The present method includes receiving a time-space searching condition and a query, and selecting a plurality of searching results from an object database in accordance with the time-space searching condition, a similarity between the query and each of a plurality of data records of a first category in the object database, and a time information and a location information corresponding to each of a plurality of data records of a second category in the object database. The method further includes receiving at least one user input corresponding to at least one of the searching results, and determining a display manner of the searching results on a user interface in accordance with the at least one user input and the similarity between the query and each searching result.