The problem SignTrack solves

Our solution idea is to develop a sign language recognition system that uses a webcam to capture sign language gestures. We will apply computer vision and machine learning techniques to analyze the gestures in real-time. The system will provide instant feedback or translation of the gestures, making sign language communication more accessible for everyone.

Challenges we ran into

we encountered a specific bug related to video streaming and real-time gesture prediction. The bug caused a delay in processing and displaying the video feed, resulting in a lag between the captured gestures and the corresponding predicted results.To overcome this hurdle, we carefully examined the code and identified the bottleneck in the processing pipeline. We optimized the code by implementing a circular buffer to store and process a fixed number of recent gesture sequences instead of processing the entire sequence repeatedly.