CN111277825A - Code stream control method based on Haisi chip - Google Patents
Code stream control method based on Haisi chip Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
- H04N19/146—Data rate or code amount at the encoder output
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
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- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/25—Determination of region of interest [ROI] or a volume of interest [VOI]
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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
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- H—ELECTRICITY
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- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
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Abstract
The invention discloses a code stream control method based on a Haesi chip, which comprises the steps of operating a humanoid detection algorithm based on the Haesi chip to obtain a humanoid detection result in a picture, operating a movement detection algorithm based on the Haesi chip to obtain a movement detection result in the picture, if the humanoid is detected, obtaining the position information of the humanoid in the picture, and if the position of the humanoid is the same as the position of the humanoid at the last time, not changing the code stream; if the position of the human figure is newly added, setting the position information of the human figure detected at this time as an ROI (region of interest) and setting a Qp (quantum dot) value of the ROI; if the positions of the human figures are reduced at this time, removing the position information of the reduced human figures, and not changing the code stream; and if no human shape is detected, acquiring the mobile detection result, and setting an ROI (region of interest) region and a background frame rate according to the mobile detection result. The invention can reduce the code rate on the premise of meeting the requirement of no change of the image quality of the humanoid region.
Description
Technical Field
The application belongs to the technical field of code rate control, and particularly relates to a code stream control method based on Haisi chips.
Background
In video coding, image quality and fluency are not always compatible. Although the h.265 video coding standard is greatly optimized relative to h.264, and can save 50% of coding rate, the requirement of high definition video service still cannot be met, so that the viewing experience of the client on the video is affected, and therefore an encoding method for effectively balancing image quality and fluency is urgently needed.
Disclosure of Invention
The application aims to provide a code stream control method based on Haisi chip, which can reduce code rate on the premise of meeting the requirement of unchanged image quality of a humanoid region.
In order to achieve the purpose, the technical scheme adopted by the application is as follows:
a code stream control method based on Haisi chip comprises the following steps:
step S1, operating a Haisi chip-based human shape detection algorithm to obtain a human shape detection result in the picture;
step S2, operating a Haesi chip-based movement detection algorithm to obtain a movement detection result in the picture;
step S3, judging whether the human shape is detected in the human shape detection result, if yes, executing the steps S4-S5; otherwise, executing step S6;
step S4, acquiring the position information of the human figure in the picture, matching the position information of all the human figures acquired this time with the position information of all the human figures acquired last time, if the positions of the human figures acquired this time are the same as the positions of the human figures acquired last time, not modifying the code stream and finishing the code stream regulation and control this time; if the position of the human figure is newly added, executing step S5; if the positions of the humanoid forms are reduced, removing the position information of the reduced humanoid forms, not changing the code stream, and finishing the regulation and control of the code stream;
step S5, setting the position information of the detected human figure as an ROI area, and setting a Qp value of the ROI area to complete the code stream regulation and control;
and step S6, obtaining the mobile detection result, and setting an ROI (region of interest) region and a background frame rate according to the mobile detection result to complete the current code stream regulation and control.
Preferably, the human shape detection algorithm identifies the recognized human shape by using independent rectangular blocks, and the human shape detection result includes the number of human shapes, and the coordinates (x, y) and the size (w, h) of the rectangular block corresponding to each human shape, where x is the x-axis coordinate of the rectangular block in the picture, y is the y-axis coordinate of the rectangular block in the picture, w is the width of the rectangular block, and h is the height of the rectangular block.
Preferably, the matching between the position information of all figures obtained this time and the position information of all figures obtained last time includes:
taking the position information of the rectangular block corresponding to the last human shape as follows: coordinates (x ', y') and size (w ', h'); the position information of the rectangular block corresponding to the current human figure is taken as follows: coordinates (x, y) and size (w, h);
calculating the displacement mv of the rectangular block at this time as follows:
Δx＝x-x′
Δy＝y-y′
Δw＝w-w′
Δh＝h-h′
obtaining the displacement mv of the rectangular block at this time, wherein the displacement mv comprises four factors of delta x, delta y, delta w and delta h;
if the four factors of the displacement mv of the rectangular block at this time are all smaller than the threshold value a, the rectangular block at this time is matched with the rectangular block at the last time; otherwise there is no match.
Preferably, the setting of the ROI region and the background frame rate according to the motion detection result includes:
step S6.1, judging whether the current picture is a static picture or a dynamic picture according to the motion detection result, and executing step S6.2 if the current picture is the static picture and keeps static for 1S or more; otherwise, executing step S6.3;
s6.2, setting the ROI as a preset minimum ROI, setting the initial coordinate of the ROI as (0,0), and setting the background frame rate as 1;
and S6.3, setting the ROI area as the whole picture, and simultaneously not controlling the background frame rate.
Preferably, the number of the moving blocks returned by the motion detection result in the dynamic picture is greater than or equal to 1, and the number of the moving blocks returned by the motion detection result in the static picture is 0.
Preferably, the size of the input picture of the Haesi chip-based motion detection algorithm is 704 × 576, the size of the macro block is 4 × 4, and the value of the SAD threshold sadTHr is set to be 30 by adopting a median method;
preferably, the Qp value is set within a preset adjustment range, the adjustment range is minQp to maxQp, the minQp is a minimum Qp value, and the maxQp is a maximum Qp value.
Preferably, the minQp value is 29, and the maxQp value is 45.
Preferably, the Haesi chip is HI3516EV 300.
According to the code stream control method based on the Haesi chip, the mobile detection result of the Haesi chip is used as the control parameter of the ROI background frame rate in code rate control, and the code rate in a static scene is reduced; the human figure detection algorithm of the Haisi chip is adopted, the returned position information of the human figure is used as the control parameter of the ROI, the ROI area is set, and the Qp value of the ROI area is reduced, so that the image quality of the human figure position is ensured; the method of detecting the existence of the human figure and then detecting the existence of the movement is used for controlling the parameters of the ROI, so that the requirement of reducing the code rate on the premise of ensuring the image quality of the human figure position is met.
Drawings
Fig. 1 is a flowchart of a code stream control method based on a haisi chip according to the present application;
FIG. 2 is a Qp-value contrast display image of an embodiment in which ROI areas are set and ROI areas are not set.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, 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 application.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description of the present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.
In one embodiment, a code stream control method based on Haisi chip is provided to meet the requirement of reducing code rate on the premise of no change of image quality of a humanoid region.
As shown in fig. 1, the code stream control method based on the haisi chip of this embodiment includes the following steps:
and step S1, operating a Haisi chip-based human shape detection algorithm to obtain a human shape detection result in the picture.
The human shape detection algorithm comprises IVP initialization during running, applies mmz memory to load Haisi resource files, obtains a frame of image from a VPSS extension channel and sends the frame of image to hi _ IVP _ process _ ex for processing, and identifies the recognized human shape by adopting an independent rectangular block so as to observe whether human shape detection is accurate or not.
And the human shape detection result includes, but is not limited to, the number of human shapes, and the coordinates (x, y) and size (w, h) of the rectangular block corresponding to each human shape, where x is the x-axis coordinate of the rectangular block in the picture, y is the y-axis coordinate of the rectangular block in the picture, w is the width of the rectangular block, and h is the height of the rectangular block.
Step S2, a motion detection algorithm based on the haisi chip is run to obtain a motion detection result in the picture.
When the motion detection algorithm is operated, the IVS _ MD is initialized, the MD channel is created, the VPSS expansion channel is created, a frame is obtained and sent to the IVS _ MD through the IVE _ DMA to serve as a current image, a frame is obtained to serve as a reference image, and a motion detection result IVE _ CCBLOB _ S is obtained through the HI _ IVS _ MD _ Process.
The size of an input picture of the Haesi chip-based motion detection algorithm is 704 × 576, the size of a macro block is 4 × 4, a median method is adopted to set the SAD threshold value sadThr to be 30, the SAD threshold value is set to control the sensitivity of motion detection, and the SAD threshold value sadThr can be debugged according to an actual scene to achieve proper sensitivity. The detection sensitivity is generally set such that movement of an object at a distance of at least 10 meters can be detected.
The Haisi chip used in the embodiment is HI3516EV300, and is abundant in resource, economical and practical. Of course, other types of Haesi chips can be used.
If the number of the moving blocks returned by the movement detection result is greater than or equal to 1, the current picture is a dynamic picture, and if the number of the moving blocks returned by the movement detection result is 0, the current picture is a static picture.
Step S3, judging whether the human shape is detected in the human shape detection result, if yes, executing the steps S4-S5; otherwise, step S6 is executed.
Step S4, acquiring the position information of the human figure in the picture, matching the position information of all the human figures acquired this time with the position information of all the human figures acquired last time, if the positions of the human figures acquired this time are the same as the positions of the human figures acquired last time, not modifying the code stream and finishing the code stream regulation and control this time; if the position of the human figure is newly added, executing step S5; if the positions of the humanoid forms are reduced, the position information of the reduced humanoid forms is removed, code stream modification is not carried out, and the code stream regulation and control at this time is finished.
It should be noted that step S4 in fig. 1 only shows one branch with the position of the new human shape, and the other two branches for ending the code stream regulation are not shown.
In one embodiment, the human form matching process is as follows:
taking the position information of the rectangular block corresponding to the last human shape as follows: coordinates (x ', y') and size (w ', h'); the position information of the rectangular block corresponding to the current human figure is taken as follows: coordinates (x, y) and size (w, h);
calculating the displacement mv of the rectangular block at this time as follows:
Δx＝x-x′
Δy＝y-y＇
Δw＝w-w＇
Δh＝h-h＇
the obtained displacement mv of the current rectangular block comprises four factors of delta x, delta y, delta w and delta h.
If the four factors of the displacement mv of the rectangular block at this time are all smaller than the threshold value a, the rectangular block at this time is matched with the rectangular block at the last time; otherwise there is no match.
Since the resolution of the picture of the human-shaped detection algorithm in this embodiment is 640 × 360, high 1/6 is set as a criterion for determining whether matching is performed, that is, the value of the threshold a is 60.
And step S5, setting the position information of the human shape detected this time as an ROI (region of interest), and setting the Qp value of the ROI to complete the code stream regulation and control this time. Wherein the QP value corresponds to the number of quantization step, and the value ranges from 0 to 51 for the luminance. The smaller the value, the smaller the quantization step size, and the higher the quantization accuracy, which means that the amount of data generated may be larger in the case of the same image quality. The quantization step size doubles for every 6 increase in QP value.
When adjusting the Qp value, the Qp value of the ROI area is reduced according to the human shape detection result so as to improve the image quality of the ROI area. And code rate control adopts a Haima VBR mode, the Qp value is changed in a preset adjusting range when being set, and the adjusting range is minQp-maxQp, so that the image quality is ensured, and meanwhile, the code stream is low.
In order to reduce the image quality of the entire screen, in one embodiment, the minimum Qp value minQp and the maximum Qp value maxQp of the entire screen are set to 29 and 45, respectively. The humanoid detection algorithm of the Haisi chip can detect 3 humanoids at most, set the coordinate size of the humanoid as the region of interest, and when setting up the Qp value of the ROI region, need to set up ROI region of I frame P frame, the Qp of setting up the region of interest is controlled as the relative Qp, the relative Qp value is set up as-3.
As shown in fig. 2, fig. 2 (upper) is a display image in which the Qp value of the ROI region is set, and fig. 2 (lower) is a display image in which the Qp value of the ROI region is not set. As can be seen from the figure, the definition of the display image with the Qp value set is significantly better than that of the display image without the Qp value set.
And step S6, obtaining the mobile detection result, and setting an ROI (region of interest) region and a background frame rate according to the mobile detection result to complete the current code stream regulation and control. The background frame rate in this embodiment is understood to be the frame rate of the background region, i.e., the region of the image from which the ROI region is removed.
In one embodiment, the setting of the ROI region and the background frame rate according to the motion detection result includes:
step S6.1, judging whether the current picture is a static picture or a dynamic picture according to the motion detection result, and executing step S6.2 if the current picture is the static picture and keeps static for 1S or more; otherwise step S6.3 is performed.
And S6.2, setting the ROI as a preset minimum ROI, setting the initial coordinate of the ROI as (0,0), and setting the background frame rate as 1. In this embodiment, setting the background frame rate to be 1 should be understood as setting the input frame rate of the background frame rate to be the original frame rate of the input image, and setting the output frame rate to be 1.
And S6.3, setting the ROI area as the whole picture, and simultaneously not controlling the background frame rate. The non-control of the background frame rate is herein understood to mean that the input frame rate and the output frame rate at which the background frame rate is set are both-1.
The adjusting step adjusts the frame rate according to the state of the picture, reduces the code stream by reducing the frame rate when the picture is changed into the dynamic picture, and immediately sets the background frame rate as the normal frame rate when the picture is changed into the dynamic picture, namely, the background frame rate is not controlled, so as to avoid the blockage of the dynamic picture.
The minimum ROI area is usually preset to be a pixel area of 16x 16.
The code stream control method based on the Haisi chip of the embodiment adopts the humanoid detection and movement detection algorithm of Haisi, and uses the code stream control mode of VBR. The overall image quality is reduced, then the human-shaped area is coded in a key mode according to the human-shaped detection result, and whether the picture is set as a background picture or not and the frame rate is set to be 1 or not is judged according to the movement detection result under the condition that the human shape is not detected, so that the requirement that the code rate is reduced due to the fact that the image quality of the human-shaped area is not changed is further met.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (9)
1. A code stream control method based on Haisi chip is characterized in that the code stream control method based on Haisi chip comprises the following steps:
step S1, operating a Haisi chip-based human shape detection algorithm to obtain a human shape detection result in the picture;
step S2, operating a Haesi chip-based movement detection algorithm to obtain a movement detection result in the picture;
step S3, judging whether the human shape is detected in the human shape detection result, if yes, executing the steps S4-S5; otherwise, executing step S6;
step S4, acquiring the position information of the human figure in the picture, matching the position information of all the human figures acquired this time with the position information of all the human figures acquired last time, if the positions of the human figures acquired this time are the same as the positions of the human figures acquired last time, not modifying the code stream and finishing the code stream regulation and control this time; if the position of the human figure is newly added, executing step S5; if the positions of the humanoid forms are reduced, removing the position information of the reduced humanoid forms, not changing the code stream, and finishing the regulation and control of the code stream;
step S5, setting the position information of the detected human figure as an ROI area, and setting a Qp value of the ROI area to complete the code stream regulation and control;
and step S6, obtaining the mobile detection result, and setting an ROI (region of interest) region and a background frame rate according to the mobile detection result to complete the current code stream regulation and control.
2. The Haisi chip-based code stream control method of claim 1, wherein the humanoid detection algorithm identifies the recognized humanoid by using independent rectangular blocks, and the humanoid detection result includes the number of humanoid, and the coordinates (x, y) and the size (w, h) of the rectangular block corresponding to each humanoid, wherein x is the x-axis coordinate of the rectangular block in the picture, y is the y-axis coordinate of the rectangular block in the picture, w is the width of the rectangular block, and h is the height of the rectangular block.
3. The code stream control method based on Haisi chip of claim 2, wherein the matching according to the position information of all the figures obtained this time and the position information of all the figures obtained last time comprises:
taking the position information of the rectangular block corresponding to the last human shape as follows: coordinates (x ', y') and size (w ', h'); the position information of the rectangular block corresponding to the current human figure is taken as follows: coordinates (x, y) and size (w, h);
calculating the displacement mv of the rectangular block at this time as follows:
Δx＝x-x′
Δy＝y-y′
Δw＝w-w′
Δh＝h-h′
obtaining the displacement mv of the rectangular block at this time, wherein the displacement mv comprises four factors of delta x, delta y, delta w and delta h;
if the four factors of the displacement mv of the rectangular block at this time are all smaller than the threshold value a, the rectangular block at this time is matched with the rectangular block at the last time; otherwise there is no match.
4. The code stream control method based on Haisi chip of claim 1, wherein the setting of the ROI area and the background frame rate according to the moving detection result comprises:
step S6.1, judging whether the current picture is a static picture or a dynamic picture according to the motion detection result, and executing step S6.2 if the current picture is the static picture and keeps static for 1S or more; otherwise, executing step S6.3;
s6.2, setting the ROI as a preset minimum ROI, setting the initial coordinate of the ROI as (0,0), and setting the background frame rate as 1;
and S6.3, setting the ROI area as the whole picture, and simultaneously not controlling the background frame rate.
5. The Haas chip-based code stream control method according to claim 4, wherein the number of the moving blocks returned by the moving detection result in the dynamic picture is greater than or equal to 1, and the number of the moving blocks returned by the moving detection result in the static picture is 0.
6. The Haas chip-based codestream control method according to claim 1, wherein the input picture size of the Haas chip-based motion detection algorithm is 704 x 576, the macroblock size is 4 x 4, and the SAD threshold sadThr is set to a value of 30 by a median method.
7. The Haas chip-based code stream control method according to claim 1, wherein the Qp value is changed within a preset adjustment range when set, the adjustment range is minQp-maxQp, the minQp is a minimum Qp value, and the maxQp is a maximum Qp value.
8. The Haas chip-based code stream control method according to claim 7, wherein the minQp value is 29, and the maxQp value is 45.
9. The Haas chip-based code stream control method according to claim 1, wherein the type of the Haas chip is HI3516EV 300.
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