JoWalk is an app aimed to help blinds to detect differences on the floor and objects
JoWalk
What is it about?
JoWalk is an app aimed to help blinds to detect differences on the floor and objects.
App Store Description
JoWalk is an app aimed to help blinds to detect differences on the floor and objects.
NOTE: JoWalk is developed to be used in a safe environment, JoWalk doesn’t detect every obstacle or subsidence and is influenced by the ambient light.
It uses AI to determine the most present pattern.
JoWalk has two modalities, accessible in rotation by a single tap on the screen:
-The first modality compares the upper area of the rear camera (that corresponds to ahead with the device horizontally positioned, screen upside) with the center area of the camera, emitting a feedback every time the detection runs (this detection interval is changeable by swiping up and down on the screen and is lowered by movement) and two feedbacks if there is a difference in the pattern recognized in front in respect to the center. You can tilt your device to explore more far area.
-The second modality compares the camera captured image by swiping down and a feedback is emitted if you are pointing to a similar image. When swiping down you will receive a feedback when the reference image is captured, about after a second swiping is completed. You can save up to 27 image patterns. Delete all swiping up. Save your vocal description waiting a bit with the screen touched at the end of the swiping down. You can change the minimum threshold swiping left and right.
To permit the app to use haptics go to Settings ->Sounds & Haptics ->System Haptics Option -> and turn on this option. If the device doesn't use haptics you will receive acoustic feedbacks. To toggle audio or haptics shake your device.
JoWalk uses AI to match areas and this causes high battery consumption at every frame analyzed, in mode 1 you can reduce this consumption lowering the frame analyzing rate, in mode 2 it detects approximately one frame per second.
The matching of images is based on DTD dataset by M.Cimpoi, S. Maji, I. Kokkinos, S. Mohamed, A. Vedaldi.
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