How to Measure Distance in Photos and Videos Using Computer Vision
Blog post from Roboflow
The blog post by Tyler Odenthal explores using computer vision to measure distances in images and videos, focusing on the application of bounding boxes and pixel-to-real-world measurement conversions. It explains key concepts such as object detection, instance segmentation, and the use of bounding boxes to determine distances between detected objects, utilizing tools like JSON and OpenCV for visualization. The post discusses converting pixel distances into practical units like inches by establishing a pixel-to-inch ratio, which is calculated using known dimensions of reference objects, such as cars or a soda can, allowing for accurate distance estimation. It also touches on challenges such as maintaining tight bounding boxes and the resolution's impact on measurement accuracy, offering suggestions for overcoming these issues, like using multiple reference objects or incorporating additional sensors like LiDAR. The article provides insights into practical applications of this method in various fields and invites readers to explore and innovate further in their own projects.