Wearable Camera Layer Segmentation for Targeted Visual Search
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Solution Overview
Problem
Existing wearable computing devices face challenges in efficiently allowing users to search for specific information in complex environments by accurately identifying the layer of interest, leading to unnecessary computational resources being expended on irrelevant searches.
Innovation Solution
A method where a wearable computing device records video data, segments it into layers, and detects a pointing object's proximity to initiate a targeted search on the relevant layer, using techniques such as edge detection and optical-flow differential to enhance accuracy and user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the wearable computing device performs search on all layers in complex environments, then the user can access information from any layer, but unnecessary computational resources are expended on irrelevant searches
Solution Approach 1:
The patent segments the visual field into multiple layers based on depth information from video data. The system divides the complex environment into foreground, midground, and background layers, allowing selective search operations on specific layers rather than processing all layers uniformly. This segmentation enables the device to focus computational resources on the user's area of interest while ignoring irrelevant layers.
Solution Approach 2:
The patent applies local quality by making different parts of the visual field have different processing priorities. The system identifies the layer containing the pointing object and applies enhanced processing (search initiation) only to that specific layer, while reducing or eliminating processing on other layers. This localized approach optimizes computational resource allocation by concentrating resources where the user needs them most.
2Ease of operation
If the wearable computing device segments video data into multiple layers, then the user can selectively search specific layers of interest, but the device complexity increases
Solution Approach 1:
The patent uses segmentation to divide video data into multiple depth-based layers, enabling precise layer selection by the user. The system processes video data to identify depth discontinuities and separates the scene into distinct layers, which are then presented to the user for selective interaction. This segmentation approach provides fine-grained control over search operations while managing complexity through automated layer detection.
Solution Approach 2:
The patent introduces an intermediary processing layer that automatically analyzes video data and generates depth-based layer representations. This intermediary system handles the complex video processing tasks, including edge detection and depth map generation, and presents simplified layer options to the user. The intermediary absorbs much of the processing complexity, making the overall system more manageable while still providing precise layer selection capabilities.
3Measurement precision
If the wearable computing device initiates search on the detected layer using pointing object proximity, then the search accuracy is improved, but the detection precision requirements increase
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously monitors the user's pointing object position and adjusts layer selection based on proximity detection. The system provides visual feedback about which layer is currently selected and responds to user pointing actions by detecting proximity to layer boundaries. This feedback loop enables accurate search target selection while accommodating natural user pointing movements and reducing the need for ultra-precise detection.
Solution Approach 2:
The patent performs preliminary action by pre-processing video data to generate depth maps and identify layer boundaries before the user interaction occurs. The system analyzes the visual scene in advance, segments it into layers, and prepares detection data structures that facilitate quick and accurate pointing object detection. This preliminary processing reduces the computational burden during real-time interaction and improves detection precision by having optimized data ready in advance.
Data Source
AI summary
Methods and devices for initiating a search are disclosed. In one embodiment, a method is disclosed that includes causing a camera on a wearable computing device to record video data, segmenting the video data into a number of layers and, based on the video data, detecting that a pointing object is in proximity to a first layer. The method further includes initiating a first search on the first layer. In another embodiment, a wearable computing device is disclosed that includes a camera configured to record video data, a processor, and data storage comprising instructions executable by the processor to segment the video data into a number of layers and, based on the video data, detect that a pointing object is in proximity to a first layer. The instructions are further executable by the processor to initiate a first search on the first layer.