OPTICAL DETECTION APPARATUS AND METHODS

• US 20180278820A1
• Filed: 12/18/2017
• Published: 09/27/2018
• Est. Priority Date: 07/01/2014
• Status: Active Grant

• Current Assignee: Brain Corporation
• Original Assignee: Brain Corporation
• Inventors: Piekniewski, Filip, Polonichko, Vadim, Izhikevich, Eugene
• Granted Patent: US 10,728,436 B2
• Time in Patent Office: Days
• CPC Class Codes: B60W 30/09 Taking automatic action to avoid collision, e.g. braking and steering
• CPC Class Codes: B60W 30/14 Adaptive cruise control
• CPC Class Codes: B60W 30/16 Control of distance between vehicles, e.g. keeping a distance to preceding vehicle
• CPC Class Codes: G01C 3/08 Use of electric radiation detectors
• CPC Class Codes: G02B 13/0015 characterised by the lens design
• CPC Class Codes: G02B 27/0075 with means for altering, e.g. increasing, the depth of field or depth of focus
• CPC Class Codes: G02B 5/204 in which spectral selection is performed by means of a conductive grid or array, e.g. frequency selective surfaces for use with wavelengths longer than the infrared light H01Q15/0006
• CPC Class Codes: G02B 7/38 measured at different points on the optical axis , e.g. focussing on two or more planes and comparing image data
• CPC Class Codes: G06V 10/431 Frequency domain transformation; Autocorrelation
• CPC Class Codes: G06V 10/446 using Haar-like filters, e.g. using integral image techniques
• CPC Class Codes: G06V 20/00 Scenes; Scene-specific elements control of digital cameras H04N23/60
• CPC Class Codes: G06V 20/10 Terrestrial scenes scenes under surveillance with static cameras G06V20/52; scenes perceived from the exterior of a vehicle G06V20/56; scenes perceived from the interior of a vehicle G06V20/59
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle
• CPC Class Codes: G06V 20/584 of vehicle lights or traffic lights
• CPC Class Codes: H01L 31/02162 for filtering or shielding light, e.g. multicolour filters for photodetectors
• CPC Class Codes: H04N 23/45 for generating image signals from two or more image sensors being of different type or operating in different modes, e.g. with a CMOS sensor for moving images in combination with a charge-coupled device [CCD] for still images
• CPC Class Codes: H04N 23/54 Mounting of pick-up tubes, electronic image sensors, deviation or focusing coils
• CPC Class Codes: H05K 999/99 dummy group

Abstract

An optical object detection apparatus and associated methods. The apparatus may comprise a lens (e.g., fixed-focal length wide aperture lens) and an image sensor. The fixed focal length of the lens may correspond to a depth of field area in front of the lens. When an object enters the depth of field area (e.g., sue to a relative motion between the object and the lens) the object representation on the image sensor plane may be in-focus. Objects outside the depth of field area may be out of focus. In-focus representations of objects may be characterized by a greater contrast parameter compared to out of focus representations. One or more images provided by the detection apparatus may be analyzed in order to determine useful information (e.g., an image contrast parameter) of a given image. Based on the image contrast meeting one or more criteria, a detection indication may be produced.

Claims

1-24. -24. (canceled)

25. A method of navigating an apparatus comprising:

obtaining at least one image associated with surroundings of the apparatus using a sensor, the apparatus comprising a controller, an actuator and the sensor;

analyzing the at least one image to detect a presence of an object in the at least one image;

determining whether the object comprises one of either a target or an obstacle; and

causing the controller to selectively activate the actuator based on the determination.

26. The method of claim 25, further comprising:

activating the apparatus between a first mode and a second mode upon detection of the object, the object comprising at least one obstacle or target;

activating the first mode upon detection that the object is an obstacle, the first mode corresponds to increasing distance between the object and the apparatus; and

activating the second mode upon detection that the object is a target, the second mode corresponds to navigating the apparatus towards the object.

27. The method of claim 25, further comprising:

analyzing a plurality of static objects to calibrate the actuator and the sensor based on;

measuring a velocity vector of the apparatus based on images and data generated by the sensor;

calculating the discrepancy between an ideal velocity vector, the ideal velocity vector comprising movement of the apparatus and the measured velocity vector of the apparatus; and

adjusting subsequent actions of the apparatus based on the calculated discrepancy.

28. The method of claim 27, further comprising:

determining the velocity vector of the apparatus based on;

obtaining, via the sensor, a plurality of images, the plurality of images comprising images of a surrounding environment of the apparatus;

identifying a stationary object or fixed point within the plurality of images from the sensor;

analyzing a first image of the plurality of images to determine a first location of the stationary object at a first duration;

analyzing a second image of the plurality of images to determine a second location of the stationary object at a second duration; and

determining a velocity vector associated with the apparatus based on the difference of the first and second positions of the stationary object in the first and second images.

29. The method of claim 25, further comprising:

adapting movement of the apparatus based on the velocity vectors of surrounding objects and the apparatus, causing the controller to activate or deactivate the actuator.

30. A non-transitory computer-readable storage medium having computer readable instructions stored thereon, that when executed by at least one processor configure the at least one processor to:

receive data from at least one sensor, the data comprising at least one image of an environment;

analyze an image, from data generated by the at least one sensor, to determine a contrast parameter criterion comprising a deviation parameter, a reference value, and/or threshold associated with object detection;

detect whether an object is present in the image from the contrast parameter meeting or exceeding a predetermined threshold; and

determine a location of the object from the contrast parameter meeting or exceeding the prescribed threshold at the location of the object.

31. The non-transitory computer-readable storage medium of claim 30, wherein the at least one processor is further configured to execute the computer readable instructions to:

receive data from the at least one sensor, the data comprising dynamic lighting parameters of the environment; and

adjust the prescribed contrast parameter threshold for object detection based on the data from the at least one sensor.

32. The non-transitory storage medium of claim 30, wherein the at least one processor is further configured to execute the computer readable instructions to:

determine a contrast parameter criterion comprising a fixed or a dynamic value from statistics of multiple images gathered by the at least one sensor.

33. The non-transitory storage medium of claim 30, wherein the at least one processor is further configured to execute the computer readable instructions to:

partition a first image into at least two sub-images, the at least two sub-images comprise different energy spectra or regions of the first image; and

apply filtering operations to the at least one of the two sub-images prior to the determination of a contrast parameter criterion.

34. The non-transitory storage medium of claim 30, wherein the at least one processor is further configured to execute the computer readable instructions to:

apply an asymmetrical filter to the at least one image received from the at least one sensor to facilitate the detection of an object at a target orientation.

35. A method for detection of objects near an apparatus, comprising:

gathering data from at least one sensor, the data comprising at least one image of an environment surrounding the apparatus;

analyzing the at least one image, to determine a contrast parameter comprising a deviation parameter, a reference value, and/or threshold associated with object detection;

determining a fixed or dynamic contrast parameter threshold based on dynamic properties of the environment; and

determining if an object is present in the image from the contrast parameter meeting or exceeding a prescribed threshold.

36. The method of claim 35, further comprising:

partitioning a first image, from the plurality of images, into at least two sub-images comprising two different energy spectra or regions of the first image; and

applying filtering and/or cropping operations to the at least one of the two sub-images prior to the determination of a contrast parameter criterion.

37. The method of claim 35, further comprising:

applying an asymmetrical filter to the data from the at least one sensor to facilitate detection of objects at a target orientation.

38. The method of claim 35, further comprising:

determining a velocity vector associated with an object based on;

obtaining a plurality of data, the data comprising images of a surrounding environment of the apparatus, from at least one sensor;

analyzing a first image of the plurality of images to determine a first location of the object taken at a first duration;

analyzing a second image of the plurality of images for a second location of the object taken at a second duration, the first location being different from the second location; and

determining a velocity vector of the object based on differences in position of the object in the first and second images.

39. The method of claim 38, further comprising:

detecting a plurality of distinguishable objects in the first and second images;

determining the locations of each of the plurality of objects in both the first and second images; and

determining velocity vectors associated with each of the plurality of objects.