Object Detection and Tracking using MediaPipe
Blog post from Google Cloud
MediaPipe, an open-source framework for constructing cross-platform multimodal applied ML pipelines, has introduced a new example of object detection and tracking. It combines a recently released box tracking solution with object detection to create a system that offers several advantages, such as maintaining object IDs across frames, reducing the need for frame-by-frame detection, and improving temporal consistency. The box tracking solution, integrated into real-time applications like Motion Stills and Google Lens, utilizes classic computer vision methods and comprises three main components: motion analysis, flow packaging, and box tracking. These components enable efficient tracking by separating motion analysis and allowing metadata caching, which supports flexible and constant computation independent of the number of tracked regions. The object detection and tracking pipeline maintains stability and reduces temporal jitter by associating tracked objects with new detections using Intersection over Union (IoU), enhancing both accuracy and efficiency on mobile devices.