CN109831672B - Motion estimation method of space-time pulse array, electronic equipment and storage medium - Google Patents
Motion estimation method of space-time pulse array, electronic equipment and storage medium Download PDFInfo
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Abstract
The invention provides a motion estimation method of a space-time pulse array, which comprises the following steps: dividing the spatio-temporal pulse array into coding cubes; determining the search ranges and the search starting points of a time domain and a space domain according to the characteristic information of the current coding cube; projecting all pulse signals in the space-time pulse array on a space plane, and then performing distance measurement and matching analysis; judging whether to terminate the search in advance or not according to a matching threshold value of the current coding cube and the reference cube, if so, terminating the search in advance, and otherwise, continuing the search until the search range is exceeded; screening an optimal reference cube; and outputting the motion estimation coding information of the space-time pulse array. The invention can effectively obtain high-precision motion vectors, and accelerates the motion estimation search process so as to solve the problems of limited coding performance and long time consumption of motion estimation in space-time pulse array coding signals.
Description
Technical Field
The invention relates to the technical field of information coding, in particular to a motion estimation method for a time-space pulse array.
Background
In recent years, space-time pulse array signal data is ubiquitous in the fields of computational neuroscience, computer vision, social media, earth atmospheric science, transportation and the like, and emerges in the form of massive data.
The space-time pulse array signal is a sparse space-time lattice described by a space-time point process model, and has abstraction, discreteness and hierarchy. The abstraction of the spatiotemporal point process is a collection of discrete point events abstracted on different time scales and spatial scales, such as nerve impulses, point clouds, social media user points, seismic event points, traffic event points, and the like; the discreteness of the pulse array signal is a discontinuous sparse lattice in time domain and space domain; the time domain hierarchy is the time of the pulse sequence and the signal frequency intensity, and the time domain event information can be mined, and the space domain hierarchy is the correlation of the space position and the signal frequency intensity, and the event hierarchy relation can be analyzed. How to encode and compress the growing pulse array signal data is a precondition for the applications of transmission, storage, analysis and the like of the space-time pulse array signal.
The pulse array signals have redundancy in time domain and space domain, the pulse array signals can be decoded by using motion vectors and residual errors, and the bit overhead of the motion vectors and the residual errors is much less than that of the original pulse signals, namely, the redundancy of the pulse arrays in the time-space domain can be reduced through motion estimation, and the compression coding efficiency is greatly improved. In fact, motion estimation is an important component of the pulse array compression processing technique. The cube matching algorithm has simple algorithm and is convenient for hardware implementation, so the encoding cube is adopted as a matching unit for motion estimation. In order to achieve the best motion estimation effect, the search for the best matching cube in the global area of the motion search has large computational complexity, and occupies almost more than half of the encoding time. Meanwhile, all search areas are quickly searched in a local area and are not traversed, some possible points are compared and matched by using a search template, a better reference cube can be found by the selection method, the speed of motion search is improved, but the defect that the best matching is missed because the search areas cannot be completely traversed exists, the best matching is easily trapped in the local best matching cube, and the coding quality of the pulse array signal is influenced to a certain extent.
Therefore, how to estimate motion information, i.e. obtain motion vectors, quickly and efficiently in a pulse array signal directly affects the performance of the encoder, including the encoding quality and the encoding speed. Meanwhile, the development of a motion estimation method of a space-time pulse array is an urgent problem to be solved.
Disclosure of Invention
The purpose of the invention is realized by the following technical scheme.
The invention provides a motion estimation method of a space-time pulse array, which can effectively obtain a high-precision motion vector and accelerate the motion estimation search process so as to solve the problems of limited coding performance and time consumption of motion estimation in space-time pulse array coding signals.
According to an aspect of the present invention, there is provided a method for motion estimation of a spatio-temporal pulse array, comprising:
dividing the spatio-temporal pulse array into coding cubes;
determining the search ranges and the search starting points of a time domain and a space domain according to the characteristic information of the current coding cube;
projecting all pulse signals in the space-time pulse array on a space plane, and then performing distance measurement and matching analysis;
judging whether the search is terminated in advance according to a matching threshold value of the current coding cube and the reference cube, if so, terminating the search in advance, and otherwise, continuing the search until the search range is exceeded;
screening an optimal reference cube;
and outputting the motion estimation coding information of the space-time pulse array.
Preferably, the space-time pulse array signal is divided into coding cubes by adopting a time domain and space domain dividing technology.
Preferably, the search ranges in the time domain and the space domain include:
a time domain searching range, wherein the searching range on the time length is determined according to the signal intensity, the pulse distribution and the motion characteristics of the current coding cube;
and the space domain searching range is determined according to the space correlation, the pulse distribution and the motion characteristics of the space-time pulse array.
Preferably, the search starting point is initialized according to motion vector information of adjacent coded cubes.
Preferably, the spatial plane projection comprises:
the x-t plane, i.e. the projection plane of the horizontal-time axis, constitutes a plurality of pulse sequences;
a y-t plane, i.e. the projection plane of the vertical axis-time axis, constituting a plurality of pulse sequences;
the x-y plane, i.e. the projection plane of the horizontal-vertical axis, constitutes a statistical histogram of the pulse frequency.
More preferably, the distance metric and matching analysis comprises:
adopting the space plane projection, mapping the space distance measurement into a plane distance measurement, and calculating the distance between the pulse sequence and the statistical histogram;
the matching analysis adopts a mode of setting a threshold value to measure whether the current coding cube and the reference cube meet the best matching.
More preferably, the screening of the best reference cube comprises:
if the matching threshold is reached, stopping searching and outputting the motion estimation coding information of the current coding cube;
and if the search range is exceeded, stopping searching, screening out the cube with the minimum matching threshold in the traversed search area, and outputting the motion estimation coding information of the cube.
More preferably, the search step size of the search range over the time length has continuity.
Preferably, the distance metric comprises:
transforming the pulse sequence into a continuous function of a multidimensional space by adopting a linear kernel function and a nonlinear kernel function, and representing the correlation measurement of the pulse sequence by utilizing the norm distance between the functions;
or a learning measurement method is adopted, and the correlation between different pulse sequences is searched by using supervised learning or unsupervised learning.
More preferably, the method for processing the polarity in the spatial plane projection includes: and assigning a value to the pulse polarity by using at least one of the mean value, the highest frequency value and the weighted mean value.
According to yet another aspect of the present invention, there is also provided an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the method for motion estimation of spatiotemporal pulse arrays as described above.
According to yet another aspect of the present invention, there is also provided a non-transitory computer readable storage medium having stored thereon a computer program, which is executed by a processor, to implement the method of motion estimation of spatio-temporal pulse arrays as described above.
The invention has the advantages that: firstly, determining a search range and a search starting point of a time domain and a space domain according to the characteristic information of a current coding cube; projection matching is carried out on the space-time asynchronous pulse array signals, so that the calculation complexity of cube matching can be effectively reduced; judging whether the current encoding cube is terminated in advance through a matching threshold value of the current encoding cube and the reference cube, if so, immediately adopting an early termination searching technology, otherwise, continuing to exceed a searching range, and screening out an optimal reference cube; and finally, outputting the coding information of the motion estimation of the pulse array. The invention can accurately obtain the high-precision motion vector, effectively reduce the redundancy of pulse signals, improve the compression ratio and accelerate the motion estimation searching process.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings.
In the drawings:
FIG. 1 is a flow chart of a method for motion estimation of spatio-temporal pulse arrays according to an embodiment of the present invention;
FIG. 2 is a diagram of a pulse array signal provided by an embodiment of the present invention;
FIG. 3 is a block diagram of a space-time pulse array signal coding unit according to an embodiment of the present invention;
FIG. 4 is a diagram of motion estimation for a coding cube according to an embodiment of the present invention;
FIG. 5 is a metrology diagram of a projection plane of a pulse array provided by an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or coupled. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
For the convenience of understanding of the embodiments of the present invention, the following description will be further explained by taking a specific embodiment as an example with reference to the drawings, and the embodiment is not to be construed as limiting the embodiments of the present invention.
The space-time pulse array signal is a sparse space-time lattice described by a space-time point process model, and has abstraction, discreteness and hierarchy. The pulse array signals have redundancy in time domain and space domain, the pulse array signals can be decoded by using motion vectors and residual errors, and the bit overhead of the motion vectors and the residual errors is much less than that of the original pulse signals, namely, the redundancy of the pulse arrays in the time-space domain can be reduced through motion estimation, and the compression coding efficiency is greatly improved. In fact, motion estimation is an important component of the pulse array compression processing technique. The cube matching algorithm has the advantages of simple algorithm, convenience for hardware implementation and the like. Therefore, the encoding cube is employed as a matching unit for motion estimation. In order to achieve the best motion estimation effect, the search for the best matching cube in the global area of the motion search has large computational complexity, and occupies almost more than half of the encoding time. Meanwhile, all search areas are quickly searched in a local area and are not traversed, some possible points are compared and matched by using a search template, a better reference cube can be found by the selection method, the speed of motion search is improved, but the defect that the best matching is missed because the search areas cannot be completely traversed exists, the best matching is easily trapped in the local best matching cube, and the coding quality of the pulse array signal is influenced to a certain extent.
Therefore, how to estimate motion information, i.e. obtain motion vectors, quickly and efficiently in a pulse array signal directly affects the performance of the encoder, including the encoding quality and the encoding speed. Meanwhile, the development of a motion estimation method of a space-time pulse array is an urgent problem to be solved.
The invention provides a motion estimation method of a space-time pulse array, and relates to the field of pulse array signal coding. The invention has the following novelty and innovativeness: a pulse array facing signal; the motion estimation search range has space-time continuity, and the optimal search range can be selected; with less computational complexity. How to encode and compress the growing pulse array signal data is a precondition for the applications of transmission, storage, analysis and the like of the space-time pulse array signal.
According to an aspect of the present invention, there is provided a method for motion estimation of a spatio-temporal pulse array, comprising:
s1, dividing the space-time pulse array into coding cubes; preferably, the space-time pulse array signal is divided into coding cubes by adopting a time domain and space domain dividing technology.
S2, determining the search range and the search starting point of a time domain and a space domain according to the characteristic information of the current coding cube; and the time domain search range determines the search range on a time length according to the signal intensity, the pulse distribution and the motion characteristic of the current coding cube, and the search step size of the search range on the time length has continuity. And the space domain searching range is determined according to the space correlation, the pulse distribution and the motion characteristics of the space-time pulse array. The search starting point is initialized according to the motion vector information of the adjacent coded cubes.
And S3, projecting all pulse signals in the space-time pulse array on a space plane, and then performing distance measurement and matching analysis.
The spatial plane projection comprises:
the x-t plane, i.e. the projection plane of the horizontal-time axis, constitutes a plurality of pulse sequences;
a y-t plane, i.e. the projection plane of the vertical axis-time axis, constituting a plurality of pulse sequences;
the x-y plane, i.e. the projection plane of the horizontal-vertical axis, constitutes a statistical histogram of the pulse frequency. More preferably, the method for processing the polarity in the spatial plane projection includes: and assigning a value to the pulse polarity by using at least one of the mean value, the highest frequency value and the weighted mean value.
The distance metric and match analysis comprising: adopting the space plane projection, mapping the space distance measurement into a plane distance measurement, and calculating the distance between the pulse sequence and the statistical histogram; the matching analysis adopts a mode of setting a threshold value to measure whether the current coding cube and the reference cube meet the best matching.
The distance metric includes: transforming the pulse sequence into a continuous function of a multidimensional space by adopting a linear kernel function and a nonlinear kernel function, and representing the correlation measurement of the pulse sequence by utilizing the norm distance between the functions; or a learning measurement method is adopted, and the correlation between different pulse sequences is searched by using supervised learning or unsupervised learning.
S4, judging whether the current encoding cube is terminated in advance or not through a matching threshold value of the current encoding cube and the reference cube, if so, terminating the search in advance, and otherwise, continuing the search until the search range is exceeded;
s5, screening an optimal reference cube; if the matching threshold is reached, stopping searching and outputting the motion estimation coding information of the current coding cube; and if the search range is exceeded, stopping searching, screening out the cube with the minimum matching threshold in the traversed search area, and outputting the motion estimation coding information of the cube.
And S6, outputting the motion estimation coding information of the space-time pulse array.
According to still another aspect of the present invention, there is also provided a method for motion estimation of a spatio-temporal pulse array, comprising: an encoding method as described above, and a decoding method as described above.
According to yet another aspect of the present invention, there is also provided an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the method for motion estimation of spatiotemporal pulse arrays as described above.
According to yet another aspect of the present invention, there is also provided a non-transitory computer readable storage medium having stored thereon a computer program, which is executed by a processor, to implement the method of motion estimation of spatio-temporal pulse arrays as described above.
Examples
Human beings have made significant progress in visual sensors, far from biological visual systems in terms of actual complex tasks. The traditional frame rate vision sensor can acquire high-definition images, but the data acquisition has the defects of large redundancy, small photosensitive dynamic range, low time domain resolution of a fixed frame rate, fuzzy motion at high speed and the like. The biological vision system has the advantages of high definition, low power consumption, strong robustness and the like, and can efficiently process optical signals, perceive complex scenes and three-dimensional information of objects, understand and recognize the scenes. A Dynamic Vision Sensor (DVS) is a Vision Sensor for simulating the mechanism of neuron pulse emission and the sensitivity of peripheral cells of retina to brightness change, the emitted nerve pulse signals are described by space-time sparse pulse array signals, and compared with a traditional fixed frame rate camera, the Dynamic Vision Sensor has the advantages of high time resolution, high Dynamic range, low power consumption and the like, and has great market application potential in the fields of unmanned driving Vision sensors, unmanned aerial vehicle Vision sensors, robot Vision navigation positioning and the like. How to encode and compress the growing pulse array signal data is a precondition for the applications of transmission, storage, analysis and the like of the space-time pulse array signal.
In order to fundamentally solve the problems of the coding performance limitation and the time consumption duration of motion estimation in the space-time pulse array coded signal, the embodiment provides a method for motion estimation of a space-time pulse array, and a flowchart is shown in fig. 1 and includes the following steps:
And step 3, determining the search ranges of the space domain and the time domain and the start point of the search according to the characteristic information of the current coding cube, as shown in fig. 4.
And 4, adopting projection matching measurement for the current coding cube and the matching cube, namely projecting the space-time pulse signals on an x-t plane, a y-t plane and an x-y plane respectively, projecting the pulses at the same positions, and assigning the polarities by adopting maximum frequency, as shown in fig. 5. Mapping the space distance of the pulse signal into the distance between the plane pulse sequence and the statistical histogram, wherein the distance measurement of the pulse sequence adopts a Gaussian kernel method with independent polarity, and the distance measurement of the statistical histogram adopts Euclidean distance, thereby matching space-time pulses with complexity O (n)3) Reduced to pulse sequence matching complexity O (n)2)。
Step 5, according to the matching degree of the current coding cube and the matching cube, if the matching degree is smaller than a threshold value, a search early termination technology is immediately adopted, namely, the search is stopped, and the motion vector information of the current cube is output; otherwise, the method continues to exceed the searching range set in the step 3.
And 6, screening out the cube corresponding to the minimum matching distortion from the search range set in the step 3, and outputting the motion vector information as the best matching cube, as shown in fig. 4.
It should be noted that:
the algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose devices may be used with the teachings herein. The required structure for constructing such a device will be apparent from the description above. Moreover, the present invention is not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components in the creation apparatus of a virtual machine according to embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A method for motion estimation of spatio-temporal pulse arrays, comprising:
obtaining a space-time pulse array, wherein the space-time pulse array is a sparse space-time lattice described by a space-time point process model;
dividing the space-time pulse array into coding cubes by adopting a time domain and space domain dividing technology;
determining the search ranges and the search starting points of a time domain and a space domain according to the characteristic information of the current coding cube;
projecting all pulse signals in the space-time pulse array on a space plane, and then performing distance measurement and matching analysis;
judging whether to terminate the search in advance or not according to a matching threshold value of the current coding cube and the reference cube, if so, terminating the search in advance, and otherwise, continuing the search until the search range is exceeded;
screening for best reference cubes, comprising: if the matching threshold is reached, stopping searching and outputting the motion estimation coding information of the current coding cube; if the search range is exceeded, stopping searching, screening out the coding cube with the minimum matching threshold value in the traversed search area, and outputting the motion estimation coding information of the coding cube;
and outputting the motion estimation coding information of the space-time pulse array.
2. The method of motion estimation of spatio-temporal pulse arrays according to claim 1,
the search ranges of the time domain and the space domain comprise:
a time domain searching range, wherein the searching range on the time length is determined according to the signal intensity, the pulse distribution and the motion characteristics of the current coding cube;
and the space domain searching range is determined according to the space correlation, the pulse distribution and the motion characteristics of the space-time pulse array.
3. The method of motion estimation of spatio-temporal pulse arrays according to claim 1,
the search starting point is initialized according to the motion vector information of the adjacent coded cubes.
4. The method of motion estimation of spatio-temporal pulse arrays according to claim 1,
the spatial plane projection comprises:
a projection plane of a horizontal-time axis constituting a plurality of pulse sequences;
a projection plane of a vertical axis-a time axis, constituting a plurality of pulse sequences;
and a projection plane of a horizontal axis and a vertical axis forms a pulse frequency statistical histogram.
5. The method of motion estimation of spatio-temporal pulse arrays according to claim 4,
the distance metric and match analysis comprising:
adopting the space plane projection, mapping the space distance measurement into a plane distance measurement, and calculating the distance between a pulse sequence and a pulse frequency statistical histogram;
the matching analysis adopts a mode of setting a matching threshold value to measure whether the current coding cube and the reference cube meet the best matching.
6. The method of motion estimation of spatio-temporal pulse arrays according to claim 2,
the search step size of the search range over the length of time has continuity.
7. The method of motion estimation of spatio-temporal pulse arrays according to claim 5,
the distance metric includes:
transforming the pulse sequence into a continuous function of a multidimensional space by adopting a linear kernel function or a nonlinear kernel function, and representing the correlation measurement of the pulse sequence by utilizing the norm distance between the functions;
or a learning measurement method is adopted, and the correlation between different pulse sequences is searched by using supervised learning or unsupervised learning.
8. The method of motion estimation of spatio-temporal pulse arrays according to claim 4,
the processing method for the polarity in the space plane projection comprises the following steps: and assigning a value to the pulse polarity by using at least one of the mean value, the highest frequency value and the weighted mean value.
9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the method of motion estimation of a spatiotemporal pulse array as claimed in any of claims 1-8.
10. A non-transitory computer-readable storage medium having stored thereon a computer program, the program being executable by a processor to implement the method for motion estimation of spatio-temporal pulse arrays according to any of claims 1-8.
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