MOTION-BASED SCENE SELECTION FOR AN AUTONOMOUS VEHICLE
Motion-based scene selection for an autonomous vehicle may include identifying, in camera data from an autonomous vehicle, based on a plurality of motion vectors associated with the camera data, one or more image objects; determining, for each image object of the one or more image objects, based on the one or more motion vectors, a corresponding label of one or more labels; and encoding the one or more labels in association with the camera data.
1 . A method for motion-based scene selection for an autonomous vehicle, the method comprising:
identifying, in camera data from an autonomous vehicle, based on a plurality of motion vectors associated with the camera data, one or more image objects;
determining, for each image object of the one or more image objects, based on the one or more motion vectors, a corresponding label of one or more labels; and
encoding the one or more labels in association with the camera data.
2 . The method of claim 1 , wherein identifying the one or more image objects comprises:
determining, for each pixel of a plurality of pixels of the camera data, a corresponding motion vector of the plurality of motion vectors; and
determining, based on the plurality of motion vectors, as the one or more image objects, one or more pixel groupings.
3 . The method of claim 1 , wherein the one or more labels indicate one or more of a speed of a corresponding object relative to the autonomous vehicle, a position of the corresponding object relative to the autonomous vehicle, or a direction of movement of the corresponding object relative to the autonomous vehicle.
4 . The method of claim 1 , further comprising:
determining, based on the one or more labels, one or more object classes for the one or more image objects; and
wherein encoding the one or more labels in association with the camera data comprises encoding the one or more object classes in association with the camera data.
5 . The method of claim 1 , wherein the camera data is included in a corpus of camera data, and the method further comprises selecting, from the corpus of camera data, based on the one or more labels, a subset of the corpus of camera data.
6 . The method of claim 5 , further comprising training, based on the selected subset of the corpus of camera data, a neural network.
7 . The method of claim 6 , wherein the trained neural network is configured to determine autonomous vehicle operational commands.
8 . An apparatus for motion-based scene selection for an autonomous vehicle, the apparatus configured to perform steps comprising:
identifying, in camera data from an autonomous vehicle, based on a plurality of motion vectors associated with the camera data, one or more image objects;
determining, for each image object of the one or more image objects, based on the one or more motion vectors, a corresponding label of one or more labels; and
encoding the one or more labels in association with the camera data.
9 . The apparatus of claim 8 , wherein identifying the one or more image objects comprises:
determining, for each pixel of a plurality of pixels of the camera data, a corresponding motion vector of the plurality of motion vectors; and
determining, based on the plurality of motion vectors, as the one or more image objects, one or more pixel groupings.
10 . The apparatus of claim 8 , wherein the one or more labels indicate one or more of a speed of a corresponding object relative to the autonomous vehicle, a position of the corresponding object relative to the autonomous vehicle, or a direction of movement of the corresponding object relative to the autonomous vehicle.
11 . The apparatus of claim 8 , wherein the steps further comprise:
determining, based on the one or more labels, one or more object classes for the one or more image objects; and
wherein encoding the one or more labels in association with the camera data comprises encoding the one or more object classes in association with the camera data.
12 . The apparatus of claim 8 , wherein the camera data is included in a corpus of camera data, and the steps further comprise selecting, from the corpus of camera data, based on the one or more labels, a subset of the corpus of camera data.
13 . The apparatus of claim 12 , wherein the steps further comprise training, based on the selected subset of the corpus of camera data, a neural network.
14 . The apparatus of claim 13 , wherein the trained neural network is configured to determine autonomous vehicle operational commands.
15 . A computer program product disposed upon a non-transitory computer readable medium, the computer program product comprising computer program instructions for motion-based scene selection for an autonomous vehicle that, when executed, cause a computer system of the autonomous vehicle to carry out the steps of:
identifying, in camera data from an autonomous vehicle, based on a plurality of motion vectors associated with the camera data, one or more image objects;
determining, for each image object of the one or more image objects, based on the one or more motion vectors, a corresponding label of one or more labels; and
encoding the one or more labels in association with the camera data.
16 . The computer program product of claim 15 , wherein identifying the one or more image objects comprises:
determining, for each pixel of a plurality of pixels of the camera data, a corresponding motion vector of the plurality of motion vectors; and
determining, based on the plurality of motion vectors, as the one or more image objects, one or more pixel groupings.
17 . The computer program product of claim 15 , wherein the one or more labels indicate one or more of a speed of a corresponding object relative to the autonomous vehicle, a position of the corresponding object relative to the autonomous vehicle, or a direction of movement of the corresponding object relative to the autonomous vehicle.
18 . The computer program product of claim 15 , wherein the steps further comprise:
determining, based on the one or more labels, one or more object classes for the one or more image objects; and
wherein encoding the one or more labels in association with the camera data comprises encoding the one or more object classes in association with the camera data.
19 . The computer program product of claim 15 , wherein the camera data is included in a corpus of camera data, and the steps further comprise selecting, from the corpus of camera data, based on the one or more labels, a subset of the corpus of camera data.
20 . The computer program product of claim 19 , wherein the steps further comprise training, based on the selected subset of the corpus of camera data, a neural network.