Systems and methods for efficiently sensing collision threats
A system for efficiently sensing collision threats has an image sensor configured to capture an image of a scene external to a vehicle. The system is configured to then identify an area of the image that is associated with homogeneous sensor values and is thus likely devoid of collision threats. In order to reduce the computational processing required for detecting collision threats, the system culls the identified area from the image, thereby conserving the processing resources of the system.
1 . A vehicular system for sensing collision threats, comprising:
a vehicle;
a first image sensor coupled to the vehicle and configured to capture a first image of a scene external to the vehicle;
a second sensor coupled to the vehicle and configured to provide sensor values based on reflections from the scene external to the vehicle;
at least one processor in communication with a non-transitory memory storing instructions, that when executed, cause the processor to:
identify a homogenous grouping of sensor values from the sensor values provided by the second sensor, wherein the homogenous grouping of sensor values correspond to a first geographic region;
identify an area of the first image associated with the first geographic region that is correlated to both (i) the homogenous grouping of sensor values provided by the second sensor and (ii) non-homogenous sensor values provided by the first image sensor;
responsive to identifying the area of the first image associated with both (i) the homogenous grouping of sensor values provided by the second sensor and (ii) the non-homogenous sensor values provided by the first sensor, cull the identified area from the first image thereby providing a filtered image;
process the filtered image to identify a collision threat within the filtered image; and
provide information indicative of the detected collision threat.
2 . The vehicular system of claim 1 , wherein the at least one processor implements a machine learning algorithm for processing the filtered image to identify the collision threat.
3 . The vehicular system of claim 1 , wherein the homogeneous grouping of sensor values correspond to pixels of the first image.
4 . The vehicular system of claim 1 , further comprising a second image sensor coupled to the vehicle and configured to capture a second image of the scene, wherein the homogeneous grouping of sensor values correspond to pixels of the second image.
5 . The vehicular system of claim 1 , wherein the second sensor is a radar sensor.
6 . The vehicular system of claim 1 , wherein the second sensor is a light detection and ranging (LiDAR) sensor.
7 . The vehicular system of claim 1 , wherein the at least one processor is configured to determine a value indicative of a homogeneity of the homogeneous grouping of sensor values and compare the value to a threshold.
8 . A vehicular system for sensing collision threats, comprising:
a vehicle;
a first image sensor coupled to the vehicle and configured to capture a first image of a scene external to the vehicle;
a second sensor coupled to the vehicle and configured to provide sensor values based on reflections from the scene external to the vehicle;
at least one processor configured to receive the first image, the at least one processor programmed with instructions that, when executed by the at least one processor, cause the at least one processor to:
identify a homogenous grouping of sensor values from the sensor values provided by the second sensor, wherein the homogenous grouping of sensor values correspond to a first geographic region;
determine whether an area of the first image is associated with the first geographic region that is correlated to both (i) the homogenous grouping of sensor values provided by the second sensor and (ii) non-homogenous sensor values provided by the first image sensor;
in response to determining that the area of the first image is associated with both (i) the homogenous grouping of sensor values provided by the second sensor and (ii) the non-homogenous sensor values provided by the first sensor, cull the area from the first image, thereby providing a filtered image;
detect a collision threat for the vehicle based on the filtered image; and
provide information indicative of the detected collision threat.
9 . The vehicular system of claim 8 , wherein the homogeneous sensor values comprise pixels of the first image.
10 . The vehicular system of claim 8 , further comprising a second image sensor coupled to the vehicle and configured to capture a second image of the scene, wherein the homogeneous grouping of sensor values correspond to pixels of the second image.
11 . The vehicular system of claim 8 , wherein the second sensor is a radar sensor.
12 . The vehicular system of claim 8 , wherein the second sensor is a light detection and ranging (LiDAR) sensor.
13 . The vehicular system of claim 8 , wherein the at least one processor is configured to determine a value indicative of a homogeneity of the homogeneous grouping of sensor values and compare the value to a threshold.
14 . A method for sensing collision threats, comprising:
capturing a first image of a scene external to a vehicle with a first image sensor;
receiving a homogenous grouping of sensor values from a second sensor based on reflections from the scene external to the vehicle, wherein the homogenous grouping of sensor values correspond to a first geographic region;
identifying, with at least one processor, an area of the first image associated with the first geographic region that is correlated to both (i) the homogenous grouping of sensor values provided by the second sensor and (ii) non-homogenous sensor values provided by the first image sensor;
responsive to identifying the area of the first image associated with both (i) the homogenous grouping of sensor values provided by the second sensor and (ii) the non-homogenous sensor values provided by the first sensor, culling the area from the first image with the at least one processor;
analyzing the first image subsequent to the culling with the at least one processor;
detecting a collision threat to the vehicle with the at least one processor based on the analyzing; and
providing, with the at least one processor, information indicative of the detected collision threat.
15 . The method of claim 14 , wherein the homogeneous grouping of sensor values correspond to pixels of the first image.
16 . The method of claim 14 , further comprising capturing a second image of the scene with a second image sensor, wherein the homogeneous grouping of sensor values correspond to pixels of the second image.
17 . The method of claim 14 , wherein the second sensor is a radar sensor.
18 . The method of claim 14 , wherein the second sensor is a light detection and ranging (LiDAR) sensor.
19 . The method of claim 14 , further comprising:
determining a value indicative of a homogeneity of the homogeneous grouping of sensor values; and
comparing the value to a threshold.