Abstract: A system and method for detecting electronic device use by a driver of a vehicle including acquiring an image including a vehicle from an associated image capture device positioned to view oncoming traffic, locating a windshield region of the vehicle in the captured image, processing pixels of the windshield region of the image for computing a feature vector describing the windshield region of the vehicle, applying the feature vector to a classifier for classifying the image into respective classes including at least classes for candidate electronic device use and candidate electronic device non-use, and outputting the classification.

Abstract: A system and method that includes training a classifier using uniquely defined landmark points along the windshield region based on an elastic deformation model. The deformation model uses mixtures of trees with a shared pool of parts and can be globally optimized with dynamic programming and still capture much relevant global elastic structure. Once a candidate area is identified in the scene, a learned threshold is applied to the classification score of the candidate area to determine if the candidate area is a windshield. The identified area is then cropped out for further downstream process.

Abstract: A method, non-transitory computer readable medium, and apparatus for detecting an object in an image are disclosed. For example, the method receives the image, calculates a score for each one of a plurality of locations in the image, performs a box plot of the score of the each one of the plurality of locations of the image, identifies an outlier score that falls outside of the box plot, determines that a distance ratio of the outlier score is less than a predefined distance ratio and detects the object in a location of the plurality of locations of the image corresponding to the outlier score.

Abstract: A method, non-transitory computer readable medium, and apparatus for detecting an object in an image are disclosed. For example, the method receives the image, calculates a score for each one of a plurality of locations in the image, performs a box plot of the score of the each one of the plurality of locations of the image, identifies an outlier score that falls outside of the box plot, determines that a distance ratio of the outlier score is less than a predefined distance ratio and detects the object in a location of the plurality of locations of the image corresponding to the outlier score.

Abstract: A system and method that includes training a classifier using uniquely defined landmark points along the windshield region based on an elastic deformation model. The deformation model uses mixtures of trees with a shared pool of parts and can be globally optimized with dynamic programming and still capture much relevant global elastic structure. Once a candidate area is identified in the scene, a learned threshold is applied to the classification score of the candidate area to determine if the candidate area is a windshield. The identified area is then cropped out for further downstream process.

Abstract: A system and method for detecting electronic device use by a driver of a vehicle including acquiring an image including a vehicle from an associated image capture device positioned to view oncoming traffic, locating a windshield region of the vehicle in the captured image, processing pixels of the windshield region of the image for computing a feature vector describing the windshield region of the vehicle, applying the feature vector to a classifier for classifying the image into respective classes including at least classes for candidate electronic device use and candidate electronic device non-use, and outputting the classification.