Indoor Rock Climbing Wall Route Displayer

The soaring popularity of rock climbing stems from the challenge of conceiving and completing routes of increasing difficulty. Separate routes on the wall are often graded by difficulty, but fluctuations in this delineation exist for different facilities and thus a standardized system can provide a more accurate and enjoyable experience for climbers. This project takes an image taken of the climbing wall by an Android phone and overlays a directed route for the user to perform. This is accomplished through utilizing a scale-invariant feature transform descriptor matching algorithm to retrieve a preconfigured route combination from a crafted database. The results show error-free detection of the climbing wall can be achieved through utilization of 5000 homography trials. Keywords—scale-invariant feature transform; SIFT; random sample consensus; homography matching; template matching; color histogram; Android application;