Motive Technologies, Inc.

Keep Truckin, Inc.

Aamer Zaheer

Ali Hassan

Ahmed Ali

Afsheen Rafaqat Ali

Syed Wajahat Ali Shah Kazmi

Hussam Ullah Khan

Seth Brandon Spiel

Numan Sheikh

Disclosed are methods, devices, and computer-readable media for detecting lanes and objects in image frames of a monocular camera. In one embodiment, a method is disclosed comprising receiving a sample set of image frames; detecting a plurality of markers in the sample set of image frames using a convolutional neural network (CNN); fitting lines based on the plurality of markers; detecting a plurality of vanishing points based on the lines; identifying a best fitting horizon for the sample set of image frames via a RANSAC algorithm; computing an inverse perspective mapping (IPM) based on the best fitting horizon; and computing a lane width estimate based on the sample set of image frames using the IPM in a rectified view and the parallel line fitting.

Lane detection and distance estimation using single-view geometry

The present disclosure relates generating a geofence based on messages received periodically from a plurality of vehicles. A candidate geofence is approximated based on vehicle stoppage data obtained from a datalog of messages. For a given candidate geofence, additional stoppage data is obtained to identify additional vehicle stoppages. The locations of these additional vehicle stoppages are binned to a corresponding geospatial tile. A relatively large cluster of contiguous geospatial tiles form a geofence that may be transmitted to a client device.

Systems and methods for generating geofences

Growing community of inventors

Lahore, Pakistan

Aamer Zaheer