Object sensing device

US9679196B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9679196-B2
Application numberUS-201414770604-A
CountryUS
Kind codeB2
Filing dateFeb 3, 2014
Priority dateFeb 27, 2013
Publication dateJun 13, 2017
Grant dateJun 13, 2017

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  1. Title

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  2. Abstract

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  4. Key dates

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  5. First independent claim

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Abstract

Official abstract text for this publication.

In order to provide an object sensing device whereby, among limited computation resources, performance is improved in sensing an object when sense processing a plurality of objects to be sensed, an object sensing device includes image capture units which capture images external to a host vehicle, and a processing device which sense processes objects to be sensed from the images which are captured by the image capture units, said processing device further including: a scene analysis unit which analyzes a travel scene of the host vehicle; a process priority change unit which changes a sensing process priority of the object to be sensed on the basis of the travel scene which is analyzed by the scene analysis unit; and an object to be sensed sensing unit which carries out a sensing of the object to be sensed on the basis of the sensing process priority which is changed by the process priority change unit.

First claim

Opening claim text (preview).

The invention claimed is: 1. An object sensing device, comprising: an image capture unit that captures surroundings of a host vehicle; and at least one processor that executes a sensing process of an object to be sensed from an image captured by the image capture unit to: analyze a travel scene of the host vehicle; change a sensing process priority of the object to be sensed based on the travel scene analyzed by the scene analysis unit; sense the object to be sensed based on the changed sensing process priority, calculate an existence probability of the object to be sensed based on map information and the analyzed travel scene using pre-stored learned data in which travel scene types, place attributes, and existence probability values are associated. 2. The object sensing device according to claim 1 , wherein the image capture unit comprises a left image capture unit and a right image capture unit, and the at least one processor executes a sensing process of the object to be sensed from a left image captured by the left image capture unit and a right image captured by the right image capture unit. 3. The object sensing device according to claim 2 , wherein the at least one processor: calculates a distance to the object to be sensed from the left image and the right image; and calculates an existence probability of the object to be sensed based on the travel scene analyzed by the scene analysis unit, wherein the at least one processor changes the sensing process priority of the object to be sensed based on the calculated existence probability, and executes a sensing process of the object to be sensed based on calculated distance information and the changed sensing process priority. 4. The object sensing device according to claim 3 , wherein the at least one processor: extracts a road region based on the left image, the right image, and the distance information; detects a parked vehicle based on the left image, the right image, and the distance information; determines attributes of places in regions outside of the road region based on the left image, the right image, and the distance information; and detects a crosswalk based on the left image, the right image, and the distance information. 5. The object sensing device according to claim 1 , wherein the at least one processor calculates an existence probability of the object to be sensed based on the analyzed travel scene, and changes the sensing process priority of the object to be sensed based on the calculated existence probability. 6. The object sensing device according to claim 5 , wherein the at least one processor generates and outputs a speed command for controlling a speed of the host vehicle based on the calculated existence probability. 7. The object sensing device according to claim 5 , wherein the at least one processor changes exposure control parameters of the image capture unit based on the calculated existence probability. 8. The object sensing device according to claim 7 , wherein if the object to be sensed is a pedestrian, the at least one processor: extracts regions in which a possibility that a pedestrian exists is high from the calculated existence probability; changes a pedestrian sensing logic that senses a pedestrian based on the regions in which a possibility that a pedestrian exists is high; performs gradation correction on an image based on the regions in which a possibility that a pedestrian exists is high; and extracts a brightness of an image from the regions in which a possibility that a pedestrian exists is high and changes exposure control parameters based on the brightness of the image. 9. The object sensing device according to claim 1 , wherein the at least one processor: acquires the map information, and wherein the at least one processor changes the sensing process priority of the object to be sensed based on the calculated existence probability. 10. The object sensing device according to claim 1 , wherein the image capture unit and the at least one processor are installed in an integrated housing or are installed in separate housings. 11. The object sensing device according to claim 1 , wherein if a pedestrian existence probability is higher than a predetermined value, the at least one processor changes the sensing process priority so that a pedestrian sensing process is executed with priority over other objects to be detected. 12. The object sensing device according to claim 11 , wherein the at least one processor changes sensing process parameters so that the pedestrian sensing process when the pedestrian existence probability is high is executed in detail. 13. The object sensing device according to claim 12 , wherein if the pedestrian existence probability is higher than the predetermined value, a command for executing speed control by suppressing acceleration of the host vehicle is generated and output to a vehicle speed control device. 14. The object sensing device according to claim 13 , wherein the pedestrian existence probability is calculated based on learned data, the learned data prepared based on one or more results of investigations conducted in advance. 15. The object sensing device according to claim 14 , wherein the learned data is included in a table, wherein a vertical axis of the table includes image scene types and a horizontal axis includes one or more attributes places where the host vehicle is traveling. 16. The object sensing device according to claim 15 , wherein the image scene types include one or more of: (i) guard rail or shrubbery, (ii) gaps between guard rail or shrubbery, (iii) crosswalks, (iv) sidewalks without guard rail, (v) parked vehicles, and (vi) gaps between parked vehicles, and wherein the one or more attributes places includes one or more of: (i) an urban area, (ii) a residential area, (iii) a commercial facility, (iv) a school, (v) highway, (vi) an elevated road, (vii) a mountainous area, and (viii) a road with few intersections. 17. The object sensing device according to claim 1 , wherein the at least one processor changes sensing process parameters so that a pedestrian sensing process when a pedestrian existence probability is high is executed in detail. 18. The object sensing device according to claim 1 , wherein if a pedestrian existence probability is higher than a predetermined value, a command for executing speed control by suppressing acceleration of the host vehicle is generated and output to a vehicle speed control device. 19. The object sensing device according to claim 1 , wherein a pedestrian existence probability is calculated based on learned data, the learned data prepared based on one or more results of investigations conducted in advance. 20. The object sensing device according to claim 19 , wherein the learned data is included in a table, wherein a vertical axis of the table includes image scene types and a horizontal axis includes one or more attributes places where the host vehicle is traveling. 21. The object sensing device according to claim 20 , wherein the image scene types include one or more of: (i) guard rail or shrubbery, (ii) gaps between guard rail or shrubbery, (iii) crosswalks, (iv) sidewalks without guard rail, (v) parked vehicles, and (vi) gaps between parked vehicles, and wherein the one or more attributes places includes one or more of: (i) an urban area, (ii) a residential area, (iii) a commercial facility, (iv) a school, (v) highway, (vi) an elevated road, (vii) a mountainous area, and (viii) a road with f

Assignees

Inventors

Classifications

  • by influencing the exposure time · CPC title

  • Probabilistic image processing · CPC title

  • Capturing isolated or intermittent images triggered by the occurrence of a predetermined event, e.g. an object reaching a predetermined position (signal generation from motion picture films H04N5/253) · CPC title

  • Stereoscopic video; Stereoscopic image sequence · CPC title

  • characterised by the type of image processing · CPC title

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What does patent US9679196B2 cover?
In order to provide an object sensing device whereby, among limited computation resources, performance is improved in sensing an object when sense processing a plurality of objects to be sensed, an object sensing device includes image capture units which capture images external to a host vehicle, and a processing device which sense processes objects to be sensed from the images which are captur…
Who is the assignee on this patent?
Hitachi Automotive Systems Ltd
What technology area does this patent fall under?
Primary CPC classification G06K9/00369. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Jun 13 2017 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).