Distributed Video Processing System with Performance-Based Worker Allocation
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Solution Overview
Problem
Outsourcing projects to cost-effective labor sources often fail to deliver promised cost savings due to inadequate management and difficulty in selecting qualified remote workers, resulting in subpar work that requires revision or rework.
Innovation Solution
A method and system for managing distributed video processing by subdividing video frames into groups, distributing them to remote workers, calculating performance ratings, and allocating subsequent projects based on these ratings, using a computer system to optimize worker selection and project management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If video frames are distributed to multiple remote workers for processing, then productivity increases through parallel processing, but quality control becomes more difficult due to varying worker skill levels and lack of oversight
Solution Approach 1:
The patent segments video frames into groups and distributes them to multiple workers based on their performance ratings. This segmentation allows parallel processing while maintaining quality control through systematic allocation - higher-rated workers receive more or more critical frame groups, ensuring that quality standards are met across the distributed workforce.
Solution Approach 2:
The system implements a feedback mechanism where worker performance is continuously monitored and rated based on the quality of processed frames. These performance ratings are then fed back into the allocation algorithm, which uses them to optimize future task distribution. This closed-loop feedback ensures that quality control improves over time as the system learns to allocate work more effectively based on demonstrated worker capabilities.
2Manufacturing precision
If performance-based allocation is implemented to improve quality, then worker motivation increases, but system complexity increases due to performance tracking and rating calculations
Solution Approach 1:
The system employs self-service mechanisms where workers automatically have their performance measured and rated based on objective metrics of their processed frames. The allocation algorithm automatically adjusts task distribution based on these ratings without requiring manual intervention or complex hierarchical management structures. This automation reduces system complexity while maintaining quality control through performance-based allocation.
3Productivity
If frames are subdivided and distributed to multiple workers, then productivity increases through parallel processing, but coordination overhead increases for managing and collecting results
Solution Approach 1:
The system performs preliminary actions by pre-calculating performance ratings and preparing allocation decisions before frames are distributed. The allocation algorithm is designed to efficiently assign frame groups to workers in advance, and the system is structured to automatically collect and process results as they come in. This preliminary preparation minimizes coordination overhead during the actual processing phase, allowing parallel processing to proceed with minimal management intervention.
Data Source
AI summary
A project network application can provide functionality for a plurality of worker systems to perform digital video editing so as to at least partially perform two- to three-dimensional conversion of a video. The project network application may, for instance, include tools for performing rotoscoping, depth mapping, object offsetting, occlusion filling, and the like.