Motive Technologies, Inc.

Disney Enterprises, Inc.

Ijaz Akhter

Ali Hassan

Afsheen Rafaqat Ali

Ahmed Ali

Muhammad Faisal

Iain Matthews

Yaser Sheikh

Hussam Ullah Khan

Tomas Simon

Sohaib Khan

Described are embodiments for training and using a close following classifier. In the example embodiments, a system includes a backbone network configured to receive an image; and at least one prediction head communicatively coupled to the backbone network, the at least one prediction head configured to receive an output from the backbone network, wherein the at least one prediction head includes a classifier configured to classify the image as including a close-following event, the classifier receiving the output of the backbone network and a vehicle speed as inputs.

Close following detection using machine learning models

Disclosed are a multi-task training technique and resulting model for detecting distracted driving. In one embodiment, a method is disclosed comprising inputting a plurality of labeled examples into a multi-task network, the multi-task network comprising: a backbone network, the backbone network generating one or more feature vectors corresponding to each of the labeled examples, and a plurality of prediction heads coupled to the backbone network; minimizing a joint loss based on outputs of the plurality of prediction heads, the minimizing the joint loss causing a change in parameters of the backbone network; and storing a distraction classification model after minimizing the joint loss, the distraction classification model comprising the parameters of the backbone network and parameters of at least one of the prediction heads.

Distracted driving detection using a multi-task training process

Techniques are disclosed for generating a bilinear spatiotemporal basis model. A method includes the steps of predefining a trajectory basis for the bilinear spatiotemporal basis model, receiving three-dimensional spatiotemporal data for a training sequence, estimating a shape basis for the bilinear spatiotemporal basis model using the three-dimensional spatiotemporal data, and computing coefficients for the bilinear spatiotemporal basis model using the trajectory basis and the shape basis.

System and method for generating bilinear spatiotemporal basis models

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Lahore, Pakistan

Ijaz Akhter