Method and system for estimating gaze direction of vehicle drivers
First Claim
1. A method for continuously monitoring the gaze direction of a driver of a vehicle over time, said method comprising:
- receiving video captured by a mobile image-capturing unit comprising camera within a vehicle, said camera of said mobile image-capturing unit mounted facing a driver of said vehicle;
extracting frames from said video;
detecting a facial region corresponding to a face of said driver within said extracted frames;
computing feature descriptors from said facial region, said feature descriptors comprising at least one feature vector comprising a multi-dimension feature vector;
normalizing each component of said at least one feature vector Including face part locations and sizes associated with said facial region to render said feature descriptors invariant to facial translations and scaling as well as pixel resolution, wherein said normalizing comprises normalizing a position and size of said face by lengths of axes of a face coordinate system defined by a square surrounding said detected face with an origin located at a top-left corner of said square; and
applying a gaze classifier with respect to said vehicle, said driver, and said camera, wherein said gaze classifier receives said feature descriptors as inputs and outputs at least one label corresponding to at least one of a predefined finite number of common driving gaze directions to identify a gaze direction of said driver of said vehicle.
9 Assignments
0 Petitions
Accused Products
Abstract
Methods and systems for continuously monitoring the gaze direction of a driver of a vehicle over time. Video is received, which is captured by a camera associated with, for example, a mobile device within a vehicle, the camera and/or mobile device mounted facing the driver of the vehicle. Frames can then be extracted from the video. A facial region can then be detected, which corresponds to the face of the driver within the extracted frames. Features descriptors can then be computed from the facial region. A gaze classifier derived from the vehicle, the driver, and the camera can then be applied, wherein the gaze classifier receives the feature descriptors as inputs and outputs at least one label corresponding to one or more predefined finite number of gaze classes to identify the gaze direction of the driver of the vehicle.
-
Citations
20 Claims
-
1. A method for continuously monitoring the gaze direction of a driver of a vehicle over time, said method comprising:
-
receiving video captured by a mobile image-capturing unit comprising camera within a vehicle, said camera of said mobile image-capturing unit mounted facing a driver of said vehicle; extracting frames from said video; detecting a facial region corresponding to a face of said driver within said extracted frames; computing feature descriptors from said facial region, said feature descriptors comprising at least one feature vector comprising a multi-dimension feature vector; normalizing each component of said at least one feature vector Including face part locations and sizes associated with said facial region to render said feature descriptors invariant to facial translations and scaling as well as pixel resolution, wherein said normalizing comprises normalizing a position and size of said face by lengths of axes of a face coordinate system defined by a square surrounding said detected face with an origin located at a top-left corner of said square; and applying a gaze classifier with respect to said vehicle, said driver, and said camera, wherein said gaze classifier receives said feature descriptors as inputs and outputs at least one label corresponding to at least one of a predefined finite number of common driving gaze directions to identify a gaze direction of said driver of said vehicle. - View Dependent Claims (2, 3, 4, 5, 6, 7)
-
-
8. A system for continuously monitoring the gaze direction of a driver of a vehicle over time, said system comprising:
-
a processor; and a non-transitory computer-usable medium embodying computer program code, said non-transitory computer-usable medium capable of communicating with said processor, said computer program code comprising instructions executable by said processor and configured for; receiving video captured by a mobile image-capturing unit comprising a camera within a vehicle, said camera of said mobile image-capturing unit mounted facing a driver of said vehicle; extracting frames from said video; detecting a facial region corresponding to a face of said driver within said extracted frames; computing feature descriptors from said facial region, said feature descriptors comprising at least one feature vector comprising a multi-dimension feature vector; normalizing each component of said at least one feature vector including face part locations and sizes associated with said facial region to render said feature descriptors invariant to facial translations and scaling as well as pixel resolution, wherein said normalizing comprises normalizing a position and size of said face by lengths of axes of a face coordinate system defined by a square surrounding said detected face with an origin located at a top-left corner of said square; and applying a gaze classifier with respect to said vehicle, said driver, and said camera, wherein said gaze classifier receives said feature descriptors as inputs and outputs at least one label corresponding to at least one of a predefined finite number of gaze classes to identify a gaze direction of said driver of said vehicle. - View Dependent Claims (9, 10, 11, 12, 13, 14)
-
-
15. A non-transitory processor-readable medium storing computer code representing instructions to cause a process for continuously monitoring the gaze direction of a driver of a vehicle over time, said computer code further comprising code to:
-
receive video captured by a mobile image-capturing unit comprising a camera within a vehicle, said camera of said mobile image-capturing unit mounted facing a driver of said vehicle; extract frames from said video; detect a facial region corresponding to a face of said driver within said extracted frames; compute feature descriptors from said facial region, said feature descriptors comprising at least one feature vector comprising a multi-dimension feature vector; normalize each component of said at least one feature vector including face part locations and sizes associated with said facial region to render said feature descriptors invariant to facial translations and scaling as well as pixel resolution, wherein said normalizing comprises normalizing a position and size of said face by lengths of axes of a face coordinate system defined by a square surrounding said defected face with an origin located at a top-left comer of said square; and apply a gaze classifier with respect to said vehicle, said driver, and said camera, wherein said gaze classifier receives said feature descriptors as inputs and outputs at least one label corresponding to at least one of a predefined finite number of gaze classes to identify a gaze direction of said driver of said vehicle. - View Dependent Claims (16, 17, 18, 19, 20)
-
Specification