Method and Apparatus for Providing Automatic Mirror Setting Via Inward Facing Cameras
A method or system is able to adjust an exterior mirror of a vehicle via an automatic mirror-setting (“AM”) model managed by a virtuous cycle containing a cloud based network (“CBN”). The system includes a set of mirrors, a set of inward facing cameras, a vehicle onboard computer (“VOC”), and AM module. In one embodiment, the mirrors, attached to a vehicle, are configured to capture at least a portion of external environment in which the vehicle operates. The inward facing cameras, mounted in the vehicle, are configured to collect internal images including operator facial features showing operator visual characteristics. VOC, which is coupled to CBN, is configured to determine operator vision metadata based on the internal images, operator visual characteristics, and historical stored data. The AM module is able to adaptively set a mirror to an optimal orientation so that area of external blind spot is minimized.
1 . A system for interactively adjusting a mirror mounted on a vehicle, comprising:
a plurality of mirrors attached to a vehicle and configured to capture at least a portion of external environment in which the vehicle operates;
a plurality of inward facing cameras mounted in the vehicle configured to collect internal images including operator facial features showing operator visual characteristics;
a vehicle onboard computer (“VOC”), coupled to a cloud based network (“CBN”) and the plurality of inward facing cameras, configured to determine operator vision metadata in accordance with the internal images, operator visual characteristics, and historical stored data; and
an automatic mirror-setting (“AM”) module coupled to the VOC and configured to adaptively set at least one of the plurality of mirrors to an optimal orientation so that area of external blind spot is reduced.
2 . The system of claim 1 , wherein the plurality of mirrors includes a left exterior side mirror, a right exterior side mirror, and an interior center mirror.
3 . The system of claim 1 , wherein the external environment includes road, nearby structures, pedestrians, traffic condition, nearby cars, and traffic lights.
4 . The system of claim 1 , wherein the plurality of inward facing cameras includes multiple exteriorly mounted image sensors capable of capturing internal images relating to position of driver relative to driver seat and interior of the vehicle.
5 . The system of claim 1 , wherein the operator visual characteristics includes number of eyes on operator facial feature.
6 . The system of claim 1 , wherein the operator visual characteristics includes peripheral vision, vision boundary, and height of visual center.
7 . The system of claim 1 , further comprising a plurality of outward facing cameras mounted on the vehicle collecting external images representing the surrounding environment in which the vehicle operates.
8 . The system of claim 7 , wherein the AM module includes at least a portion of an AM model which is able to dynamically adjust orientation of at least one of the plurality of mirrors to show an event associated with the external environment based on the external images and historical data from the CBN.
9 . The system of claim 8 , wherein the AM model includes an abnormal tracking function which is able to realign orientation of at least one of the plurality of mirror to continuously track an abnormal event in response to the external images and real-time cloud data submitted by other nearby vehicles.
10 . The system of claim 8 , wherein the AM model is trained by a machine learning center (“MLC”) which is coupled to the VOC and configured to train and improve the AM model based on the labeled data from the CBN.
11 . The system of claim 10 , wherein the CBN is wireles sly coupled to the VOC and configured to correlate and generate labeled data associated with AM data based on historical cloud data, internal images, and external images.
12 . The system of claim 8 , wherein the plurality of outward facing cameras is configured to capture real-time images as the vehicle moves across a geographical area.
13 . The system of claim 1 , wherein the plurality of inward facing cameras is configured to extract metadata associated with operator head pose, gaze direction, and looking at a mobile device.
14 . A method for interactively setting a mirror mounted on a vehicle via metadata extraction utilizing a virtuous cycle including sensors, machine learning center (“MLC”), and cloud based network (“CBN”), comprising:
receiving a mirror resetting signal indicating at least one of a plurality of mirrors mounted on a vehicle requiring an adjustment;
activating at least a portion of inward facing cameras mounted in the vehicle for capturing internal images including driver eye level with respect to interior of the vehicle;
obtaining historical cloud data associated with the vehicle and driver from a virtuous cycle; and
adjusting at least one of the plurality of mirrors to an orientation with minimal blind spot in accordance with driver head position shown in the internal image and historical cloud data.
15 . The method of claim 14 , further comprising obtaining internal images continuously for a predefined wait period until the driver settling down before calculating driver head position.
16 . The method of claim 14 , further comprising activating a set of outward facing cameras mounted on a vehicle for recording external surrounding images representing a geographic environment in which the vehicle operates.
17 . The method of claim 14 , further comprising tracking surrounding environmental event in accordance with the external surrounding images and historical data supplied by the virtuous cycle.
18 . A method configured to utilizing one of external mirror mounted on a vehicle to dynamically track an abnormal event facilitated by an automatic mirror-setting (“AM”) model via a virtuous cycle containing sensors, machine learning center (“MLC”), and cloud based network (“CBN”), comprising:
receiving a message of detecting an abnormal event nearby surrounding area in which the vehicle operates from cloud based data pushed by the MLC;
obtaining images showing driver head position captured by a set of interior cameras while the driver operates moving vehicle;
adaptively adjusting orientation of at least one mirror to track the abnormal event based on projected location according to the message so that the driver is able to see the abnormal event.
19 . The method of claim 18 , further comprising issuing a notice of watching the abnormal event at reoriented mirror to the driver.
20 . The method of claim 19 , further comprising uploading the labeled data representing driver reaction responding to the abnormal event back to the CBN for facilitating AM model training at the MLC.