Camera Tracking via Identifying Features for Line of Sight
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Solution Overview
Problem
Existing surveillance cameras with pan, tilt, and zoom capabilities lack the ability to track specific moving entities, instead only tracking general movements or fast-moving objects, failing to target stationary entities effectively.
Innovation Solution
Programming a video camera to track a specific target entity using identifying features such as barcodes, QR codes, RFID tags, colors, or patterns, allowing it to locate and follow the entity even when stationary or obscured, using integrated readers and software applications for image or signal recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing surveillance cameras track general movements or fast-moving entities, then they can monitor activities in the vicinity, but they cannot track specific stationary target entities effectively
Solution Approach 1:
The patent segments the tracking function by introducing identifying features (barcodes, QR codes, RFID tags, colors, patterns) that can be attached to or inherent in specific target entities. This allows the camera system to distinguish and track individual targets independently, resolving the contradiction between precise targeting and versatile tracking capability
Solution Approach 2:
The patent introduces identifying features as intermediaries between the camera system and target entities. These features serve as mediators that enable the camera to recognize and track specific entities by detecting their unique identifiers, thus achieving both precise targeting and adaptable tracking of multiple different entities
2Measurement precision
If a camera tracks an entity requiring line of sight (such as barcode or QR code), then it can precisely identify the target, but it cannot track the entity when obscured or behind other objects
Solution Approach 1:
The patent applies multiple types of identifying features (barcodes, QR codes, RFID tags, colors, patterns) that can be used in different scenarios. Some features like RFID tags provide non-line-of-sight capability while others like barcodes provide precise visual identification. This multi-functional approach ensures tracking continuity even when line-of-sight features are obscured
Solution Approach 2:
The system prepares for potential line-of-sight blockages by having multiple identifying feature types available and by implementing reacquisition logic that can detect and reacquire obscured targets. This cushioning approach ensures tracking reliability even when visual identification is temporarily blocked
3Reliability
If a camera is programmed to track a specific entity with an identifying feature, then it can continuously monitor that entity, but it cannot track entities without such features or distinguish them from the target
Solution Approach 1:
The patent applies local quality by making specific target entities possess unique identifying features (barcodes, QR codes, RFID tags, specific colors, patterns) that distinguish them from other entities. This allows the camera to reliably identify and track the specific target while ignoring or differently processing entities without these features, thus maintaining tracking consistency without sacrificing the ability to recognize and differentiate between multiple entity types
Data Source
AI summary
In one embodiment, one or more computing devices receive an identifying feature of a target entity, the identifying feature requiring that the target entity to be in a line of sight of a camera for the camera to recognize the identifying feature; locate the target entity using the camera based on the identifying feature; and track the target entity using the camera based on the identifying feature.