Algorithm Real-Time Optimization
Majid Geravand
Project Objective:
To significantly enhance the performance of the existing tracking system by optimizing its architecture, algorithms, and computational resources to achieve a sustained frame rate of 200 frames per second (FPS). This optimization will enable real-time, high-precision tracking capabilities for demanding rapid object detection and localization.
Problem Statement:
The current tracking system exhibits performance limitations, hindering its application in scenarios requiring real-time responsiveness and high accuracy. By identifying and addressing bottlenecks in the system, we aim to reduce latency, improve tracking precision, and enable smooth operation at a target frame rate of 200 FPS.
Outcomes:
A significantly optimized tracking system capable of achieving a sustained frame rate of 200 FPS. Reduced latency in object detection and localization.
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Posted Aug 12, 2024
Enhance architecture, algorithms, and hardware to achieve a sustained 200 FPS frame rate. Improve accuracy, and enable high-precision object tracking.
