Distributed Pixel Processing for Mobile Image Data
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Solution Overview
Problem
Current mobile devices face challenges in processing the vast volume of image data from cameras to provide real-time object recognition and augmented reality feedback, leading to a disconnect between the potential of high-quality image data and the device's ability to effectively utilize it.
Innovation Solution
A distributed network of pixel processing engines is implemented, where basic content filtering and classification occur on the mobile device, with routing instructions sent to cloud-based services for further processing, enabling fast and interactive visual data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If all image data processing is performed on the mobile device, then processing speed is improved, but device complexity and energy consumption increase
Solution Approach 1:
The patent segments the image processing workload into two parts: basic content filtering and classification are performed on the mobile device, while more complex processing tasks are routed to cloud-based services. This segmentation allows the device to handle only essential processing locally, reducing device complexity while maintaining acceptable processing speed for basic operations.
2Power
If complex processing tasks are performed on the mobile device, then processing capability is improved, but energy consumption increases
Solution Approach 1:
The patent divides processing tasks by complexity, assigning energy-intensive complex tasks to cloud-based services while the mobile device handles only basic filtering and classification. This segmentation reduces the energy consumption of the mobile device while maintaining overall processing capability through cloud assistance.
Solution Approach 2:
The patent introduces cloud-based services as an intermediary to handle complex processing tasks. The mobile device communicates with these external services, which perform the computationally intensive work, thereby reducing the energy burden on the mobile device while maintaining high processing capability for complex operations.
3Power
If cloud-based services are used for processing, then processing capability is improved, but response time increases
Solution Approach 1:
The patent segments processing tasks by urgency and complexity, performing basic content filtering and classification immediately on the device for fast response, while routing non-urgent complex tasks to the cloud. This segmentation ensures that time-critical operations complete quickly while less urgent tasks utilize cloud resources, balancing response time and processing capability.
Data Source
AI summary
Mobile phones and other portable devices are equipped with a variety of technologies by which existing functionality can be improved, and new functionality can be provided. Some aspects relate to visual search capabilities, and determining appropriate actions responsive to different image inputs. Others relate to processing of image data. Still others concern metadata generation, processing, and representation. Yet others concern user interface improvements. Other aspects relate to imaging architectures, in which a mobile phone's image sensor is one in a chain of stages that successively act on packetized instructions/data, to capture and later process imagery. Still other aspects relate to distribution of processing tasks between the mobile device and remote resources (“the cloud”). Elemental image processing (e.g., simple filtering and edge detection) can be performed on the mobile phone, while other operations can be referred out to remote service providers. The remote service providers can be selected using techniques such as reverse auctions, through which they compete for processing tasks. A great number of other features and arrangements are also detailed.