CN112308015A - Novel depth recovery scheme based on 3D structured light - Google Patents
Novel depth recovery scheme based on 3D structured light Download PDFInfo
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- CN112308015A CN112308015A CN202011296449.9A CN202011296449A CN112308015A CN 112308015 A CN112308015 A CN 112308015A CN 202011296449 A CN202011296449 A CN 202011296449A CN 112308015 A CN112308015 A CN 112308015A
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- 238000011084 recovery Methods 0.000 title claims abstract description 14
- 238000000034 method Methods 0.000 claims abstract description 3
- 238000012545 processing Methods 0.000 claims description 13
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000012805 post-processing Methods 0.000 claims description 3
- 238000007781 pre-processing Methods 0.000 claims description 3
- 238000013461 design Methods 0.000 abstract description 3
- 238000004519 manufacturing process Methods 0.000 abstract description 2
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30196—Human being; Person
- G06T2207/30201—Face
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/24—Aligning, centring, orientation detection or correction of the image
- G06V10/247—Aligning, centring, orientation detection or correction of the image by affine transforms, e.g. correction due to perspective effects; Quadrilaterals, e.g. trapezoids
Abstract
The invention discloses a novel depth recovery scheme based on 3D structured light, which comprises the following steps: when the system starts to operate, acquiring template data and calibration parameters corresponding to the module, initializing the algorithm module, and enabling the algorithm module to enter a state of waiting for the input of an original infrared data stream; after receiving the original infrared data stream, the algorithm converts the original infrared data stream into a data format which can be processed by an algorithm core module, and then original image data processed by the algorithm is obtained. The 3D data acquisition requirement can be realized on high-pass platforms and the like, various application scene requirements of the face recognition equipment are realized by combining with rear-end application, the platform only needs to support a common camera interface and does not need to support a USB interface like application in the market, the application scene is wide, and the applicability and the practicability of the device are further improved; through reducing module paster process, reduction in production cost reduces face identification equipment's use cost and 3D module hardware design cost simultaneously.
Description
Technical Field
The invention relates to the technical field of teaching aids, in particular to a novel depth recovery scheme based on 3D structured light.
Background
At present, the depth recovery of the 3D structured light module used in the face recognition device needs to use a special ASIC chip, and an additional data conversion chip is needed to transfer the recovered data to a USB port for transmission to a master control, so that the cost of the module is greatly increased, and meanwhile, the size of the module is limited due to the relatively large size of the ASIC chip, so that the requirement that the size of the 3D module is smaller and smaller in the movement of the face recognition mobile device cannot be met, therefore, the invention designs a novel depth recovery scheme based on the 3D structured light to solve the problems in the prior art.
Disclosure of Invention
The present invention is directed to a novel depth recovery scheme based on 3D structured light, so as to solve the problems mentioned in the background art.
2. In order to achieve the purpose, the invention provides the following technical scheme: a novel depth recovery scheme based on 3D structured light, comprising the steps of:
firstly, when a system starts to operate, acquiring template data and calibration parameters corresponding to a module, initializing an algorithm module, and then enabling the algorithm module to enter a state of waiting for input of an original infrared data stream;
step two: after receiving the original infrared data stream, the algorithm converts the original infrared data stream into a data format which can be processed by an algorithm core module, and then original image data processed by the algorithm is obtained;
step three: collecting data stream through a color camera, and receiving the data stream into a system driving layer;
step four: simultaneously acquiring depth original data by the infrared camera, and receiving a depth original data stream into a system driving layer;
step five: the collected color camera data is processed by the system image processing unit and then transmitted into the middle layer
Preprocessing raw image data involves the following steps:
firstly, performing parallax recovery processing on original image data;
secondly, performing parallax post-processing on the original image;
carrying out receiving lens calibration and anti-distortion processing on the original data;
step six: performing depth calculation on the preprocessed parallax image to obtain depth data, namely outputting the depth data corresponding to the original data by an algorithm, and transmitting the depth data to the middle layer;
step seven: and the middle layer transmits the color data stream processed by the image processing unit and the depth data stream obtained by the algorithm to the frame layer and then to the back end application.
Compared with the prior art, the invention has the following beneficial effects:
the 3D data acquisition requirement can be realized on high-pass platforms and the like, various application scene requirements of the face recognition equipment are realized by combining with rear-end application, the platform only needs to support a common camera interface and does not need to support a USB interface like application in the market, the application scene is wide, and the applicability and the practicability of the device are further improved; by reducing the module pasting process, the production cost is reduced, and the use cost of the face recognition equipment and the design cost of 3D module hardware are reduced, so that the device is convenient to popularize and use; and the later-stage depth recovery algorithm of the device is relatively simple to upgrade, and the maintenance cost and the maintenance difficulty are reduced.
Drawings
Fig. 1 is a schematic diagram of the application principle of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, an embodiment of the present invention: a novel depth recovery scheme based on 3D structured light, comprising the steps of:
firstly, when a system starts to operate, acquiring template data and calibration parameters corresponding to a module, initializing an algorithm module, and then enabling the algorithm module to enter a state of waiting for input of an original infrared data stream;
step two: after receiving the original infrared data stream, the algorithm converts the original infrared data stream into a data format which can be processed by an algorithm core module, and then original image data processed by the algorithm is obtained;
step three: collecting data stream through a color camera, and receiving the data stream into a system driving layer;
step four: simultaneously acquiring depth original data by the infrared camera, and receiving a depth original data stream into a system driving layer;
step five: the collected color camera data is processed by the system image processing unit and then transmitted into the middle layer
Preprocessing raw image data involves the following steps:
firstly, performing parallax recovery processing on original image data;
secondly, performing parallax post-processing on the original image;
carrying out receiving lens calibration and anti-distortion processing on the original data;
step six: performing depth calculation on the preprocessed parallax image to obtain depth data, namely outputting the depth data corresponding to the original data by an algorithm, and transmitting the depth data to the middle layer;
step seven: and the middle layer transmits the color data stream processed by the image processing unit and the depth data stream obtained by the algorithm to the frame layer and then to the back end application.
The working principle is as follows: the data stream collected by the color camera is received and enters the system driving layer, the depth original data stream collected by the infrared camera enters the system driving layer, the collected color camera data is processed by the system image processing unit and then is transmitted into the middle layer, and the collected infrared camera data is transmitted to the depth algorithm module after being processed by the bypass.
Although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that various changes in the embodiments and/or modifications of the invention can be made, and equivalents and modifications of some features of the invention can be made without departing from the spirit and scope of the invention.
Claims (1)
1. A novel depth recovery scheme based on 3D structured light is characterized in that: the method comprises the following steps:
firstly, when a system starts to operate, acquiring template data and calibration parameters corresponding to a module, initializing an algorithm module, and then enabling the algorithm module to enter a state of waiting for input of an original infrared data stream;
step two: after receiving the original infrared data stream, the algorithm converts the original infrared data stream into a data format which can be processed by an algorithm core module, and then original image data processed by the algorithm is obtained;
step three: collecting data stream through a color camera, and receiving the data stream into a system driving layer;
step four: simultaneously acquiring depth original data by the infrared camera, and receiving a depth original data stream into a system driving layer;
step five: the collected color camera data is processed by the system image processing unit and then transmitted into the middle layer
Preprocessing raw image data involves the following steps:
firstly, performing parallax recovery processing on original image data;
secondly, performing parallax post-processing on the original image;
carrying out receiving lens calibration and anti-distortion processing on the original data;
step six: performing depth calculation on the preprocessed parallax image to obtain depth data, namely outputting the depth data corresponding to the original data by an algorithm, and transmitting the depth data to the middle layer;
step seven: and the middle layer transmits the color data stream processed by the image processing unit and the depth data stream obtained by the algorithm to the frame layer and then to the back end application.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202011296449.9A CN112308015A (en) | 2020-11-18 | 2020-11-18 | Novel depth recovery scheme based on 3D structured light |
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| CN202011296449.9A CN112308015A (en) | 2020-11-18 | 2020-11-18 | Novel depth recovery scheme based on 3D structured light |
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105120257A (en) * | 2015-08-18 | 2015-12-02 | 宁波盈芯信息科技有限公司 | Vertical depth sensing device based on structured light coding |
| CN105931240A (en) * | 2016-04-21 | 2016-09-07 | 西安交通大学 | Three-dimensional depth sensing device and method |
| WO2018006481A1 (en) * | 2016-07-04 | 2018-01-11 | 中兴通讯股份有限公司 | Motion-sensing operation method and device for mobile terminal |
| CN108363482A (en) * | 2018-01-11 | 2018-08-03 | 江苏四点灵机器人有限公司 | A method of the three-dimension gesture based on binocular structure light controls smart television |
| CN108986197A (en) * | 2017-11-30 | 2018-12-11 | 成都通甲优博科技有限责任公司 | 3D skeleton line construction method and device |
| CN109741405A (en) * | 2019-01-21 | 2019-05-10 | 同济大学 | A kind of depth information acquisition system based on dual structure light RGB-D camera |
| CN109923500A (en) * | 2016-08-22 | 2019-06-21 | 奇跃公司 | Augmented reality display device with deep learning sensor |
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2020
- 2020-11-18 CN CN202011296449.9A patent/CN112308015A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105120257A (en) * | 2015-08-18 | 2015-12-02 | 宁波盈芯信息科技有限公司 | Vertical depth sensing device based on structured light coding |
| CN105931240A (en) * | 2016-04-21 | 2016-09-07 | 西安交通大学 | Three-dimensional depth sensing device and method |
| US20170310946A1 (en) * | 2016-04-21 | 2017-10-26 | Chenyang Ge | Three-dimensional depth perception apparatus and method |
| WO2018006481A1 (en) * | 2016-07-04 | 2018-01-11 | 中兴通讯股份有限公司 | Motion-sensing operation method and device for mobile terminal |
| CN109923500A (en) * | 2016-08-22 | 2019-06-21 | 奇跃公司 | Augmented reality display device with deep learning sensor |
| CN108986197A (en) * | 2017-11-30 | 2018-12-11 | 成都通甲优博科技有限责任公司 | 3D skeleton line construction method and device |
| CN108363482A (en) * | 2018-01-11 | 2018-08-03 | 江苏四点灵机器人有限公司 | A method of the three-dimension gesture based on binocular structure light controls smart television |
| CN109741405A (en) * | 2019-01-21 | 2019-05-10 | 同济大学 | A kind of depth information acquisition system based on dual structure light RGB-D camera |
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