{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/e44c35ec0c944b599ca8e2982694145c\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/e44c35ec0c944b599ca8e2982694145c-36957197704cde07.gif","duration":246.038,"title":"DSAI Lab Project - Group 4 - Indoor Navigation for Vision Impaired ","description":"Hi everyone, I am Saran Saini, and I am demonstrating my DSAI Lab project on navigation assistance for visually impaired people in an indoor space. My pipeline takes an RGB frame and runs YOLO object detection and a depth map in parallel, then combines them into depth maps with bounding boxes. From that, I compute hazard zones, including a walkable zone of 40 percent and later zones of 30 percent, and select the layer with the lowest risk. I generate a navigation command and pass it to a TTS module for audio guidance. I deployed the app on HuggingFace, and you can analyze your own images by clicking Analyze Environment."}