Information processing device, information processing method, and program

Abstract

[Problem] To provide a novel and improved information processing device, an information processing method, and a program, which are capable of improving robustness of a camera with regard to rotation, when identifying stars corresponding to bright points. [Solution] An information processing device according to the present invention includes a detecting unit that detects a plurality of bright points from an image obtained by a camera photographing space, a calculating unit that calculates a first amount of characteristics indicating a positional relation of at least two or more bright points out of the plurality of bright points detected by the detecting unit, and an identifying unit that identifies a star corresponding to at least one bright point among the two or more bright points, on the basis of the first amount of characteristics calculated by the calculating unit, and a second amount of characteristics including, based on celestial object position information of each of at least two or more stars, a central angle in an equatorial coordinate system among the stars.

Description

[Technical field]

[0001] The present disclosure relates to an information processing device, an information processing method, and a program. [Background technology]

[0002] In recent years, a technology has been developed for identifying stars corresponding to bright spots included in an image captured in space. For example, Patent Document 1 discloses a technology for calculating the angles (separation angles) between multiple bright spots included in an image and the vector differences between the bright spots as feature quantities, and for identifying the stars corresponding to the bright spots from the feature quantities. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 10-72000 Summary of the Invention [Problem to be solved by the invention]

[0004] However, in the technology described in Patent Document 1, the feature values ​​used to identify stars fluctuate when the camera is rotated, even when the same bright spot is being identified, so it was necessary to also use an estimation function to estimate the amount of camera rotation.

[0005] Therefore, the present disclosure proposes a new and improved information processing device, information processing method, and program that can improve robustness against camera rotation when identifying a star corresponding to a bright point. [Means for solving the problem]

[0006] According to the present disclosure, there is provided an information processing device comprising: a detection unit that detects a plurality of bright spots from an image obtained by a camera capturing space; a calculation unit that calculates a first feature amount indicating a positional relationship of at least two or more bright spots among the plurality of bright spots detected by the detection unit; and an identification unit that identifies a star corresponding to at least one of the two or more bright spots based on the first feature amount calculated by the calculation unit and a second feature amount including a central angle in an equatorial coordinate system between each of the at least two or more stars based on celestial position information of the at least two or more stars.

[0007] In addition, according to the present disclosure, there is provided an information processing method executed by a computer, including detecting a plurality of bright spots from an image obtained by a camera capturing space, calculating a first feature amount indicating a positional relationship of at least two or more of the detected bright spots, and identifying a star corresponding to at least any of the two or more bright spots based on the calculated first feature amount and a second feature amount including a central angle in an equatorial coordinate system between each of the at least two or more stars based on celestial position information of each of the at least two or more stars.

[0008] In addition, according to the present disclosure, a program is provided that causes a computer to realize a detection function of detecting a plurality of bright spots from an image obtained by a camera photographing space, a calculation function of calculating a first feature amount indicating a positional relationship of at least two or more bright spots among the plurality of bright spots detected by the detection function, and an identification function of identifying a star corresponding to at least one of the two or more bright spots based on the first feature amount calculated by the calculation function and a second feature amount including a central angle in an equatorial coordinate system between each of the at least two or more stars based on celestial position information of each of the at least two or more stars. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is an explanatory diagram illustrating an example of an information processing system according to the present disclosure. [Diagram 2] 2 is an explanatory diagram for explaining an example of a functional configuration of an information processing device 10 according to the present disclosure. FIG. [Diagram 3] 2 is an explanatory diagram for explaining an example of a database held by a star feature storage unit 101. FIG. [Figure 4A] 11 is an explanatory diagram for explaining an example of selection of a first bright point according to the present disclosure. FIG. [Figure 4B] 11 is an explanatory diagram for explaining an example of selection of a second bright point according to the present disclosure. FIG. [Figure 4C] 13 is an explanatory diagram for explaining an example of selection of a third bright point according to the present disclosure. FIG. [Figure 4D] FIG. 11 is an explanatory diagram for explaining an example of selection of a fourth bright point according to the present disclosure. [Figure 4E] FIG. 11 is an explanatory diagram for explaining an example of selection of a fifth bright point according to the present disclosure. [Diagram 5] 4 is an explanatory diagram for explaining an example of a feature amount calculated by a feature amount calculation unit 205. FIG. [Figure 6] 1 is an explanatory diagram for explaining an example of a database in which the star group feature storage unit 105 stores star groups and feature amounts in association with each other; FIG. [Figure 7] FIG. 11 is an explanatory diagram for explaining an example of a method for calculating a great circle distance D1 based on celestial position information. [Figure 8] FIG. 11 is an explanatory diagram for explaining an example of a method for calculating the angle AD1 based on celestial position information. [Figure 9] 2 is an explanatory diagram for explaining an example of operation processing of the information processing device 10 according to the present disclosure. FIG. [Figure 10] 1 is a block diagram showing a hardware configuration of an information processing device 10 according to the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In this specification and the drawings, components having substantially the same functional configurations are denoted by the same reference numerals, and redundant description will be omitted.

[0011] The "Mode for Carrying Out the Invention" will be described in the following item order. 1. Overview of the information processing system 2. Example of functional configuration of information processing device 10 3.Details 3.1. Calculation of Features 3.2. Advance preparation 3.3. Identifying Stars 3.4.Pose estimation 4. Example of operation processing 5. Examples of effects 6. Hardware configuration example 7. Supplementary Information

[0012] <<1. Overview of the information processing system>> As one embodiment of the present disclosure, a mechanism for improving robustness against camera rotation when identifying a star corresponding to a bright point will be described.

[0013] 1 is an explanatory diagram for explaining an example of an information processing system according to the present disclosure. The information processing system according to the present disclosure includes an artificial satellite 1, a camera 5, and an information processing device 10.

[0014] (Satellite 1) The artificial satellite 1 is a spacecraft that exists outside the Earth's atmosphere. The artificial satellite 1 may be, for example, an orbiting satellite or a geostationary satellite, or may be a space probe that performs a mission outside the Earth's central orbit. The size of the artificial satellite 1 is not limited. For example, the artificial satellite 1 may be a large spacecraft such as the International Space Station, or a small spacecraft such as a CanSat.

[0015] The artificial satellite 1 also includes a camera 5 and an information processing device 10. In this specification, an example in which the camera 5 and the information processing device 10 are separately mounted on the artificial satellite 1 will be described, but the information processing device 10 may also include the camera 5.

[0016] (Camera 5) The camera 5 photographs the universe and acquires an image including the fixed star S. The camera 5 also outputs the acquired image to the information processing device 10. In the following description, the fixed star S in the image acquired by photographing with the camera 5 may be expressed as a bright point.

[0017] The information processing device 10 detects a plurality of bright points from the image input from the camera 5. The information processing device 10 also calculates a feature amount indicating a positional relationship between at least two or more bright points, and identifies a star corresponding to at least one of the two or more bright points used in calculating the feature amount based on the calculated feature amount.

[0018] An example of the information processing system according to the present disclosure has been described above. Next, an example of the functional configuration of the information processing device 10 according to the present disclosure will be described with reference to FIG.

[0019] <<2. Example of Functional Configuration of Information Processing Device 10>> 2 is an explanatory diagram for explaining an example of a functional configuration of the information processing device 10 according to the present disclosure. As shown in FIG. 2, the information processing device 10 according to the present disclosure includes a storage unit 100 and a control unit 200.

[0020] (Storage unit 100) The storage unit 100 holds software and various data. The storage unit 100 includes a star feature storage unit 101 and a star group feature storage unit 105, as shown in FIG.

[0021] {Star feature memory unit 101} The star feature amount storage unit 101 holds a database in which stars are associated with celestial position information of the stars. An example of the database held by the star feature amount storage unit 101 will be described with reference to FIG.

[0022] 3 is an explanatory diagram for explaining an example of a database stored in the star feature storage unit 101. The star feature storage unit 101 stores a database in which various information included in, for example, the Hipparcos star catalog is extracted. The various information includes, for example, HIP numbers and the right ascension and declination of the stars indicated by each HIP number.

[0023] The HIP number is an identification number given to each star. Right ascension and declination are values ​​that represent the position of a star in the equatorial coordinate system. In the following explanation, right ascension and declination may be collectively referred to as celestial position information.

[0024] The above describes an example of the database stored in the star feature storage unit 101. The following describes the functional configuration example of the information processing device 10 with reference to FIG.

[0025] {Star group feature storage unit 105} The star group feature storage unit 105 holds a database in which at least two or more stars held in the star feature storage unit 101 are associated with feature amounts including the central angles between the two or more stars in the equatorial coordinate system. Details of the database held in the star group feature storage unit 105 will be described later. The feature amounts held in the star group feature storage unit 105 are an example of second feature amounts.

[0026] (Control unit 200) The control unit 200 controls the overall operation of the information processing device 10 according to the present disclosure. The control unit 200 has a bright point detection unit 201, a feature amount calculation unit 205, a star identification unit 209, and an attitude estimation unit 213, as shown in FIG.

[0027] {Bright spot detection unit 201} The bright spot detection unit 201 detects multiple bright spots from an image captured by the camera 5 of the universe. The multiple bright spots may be all the bright spots included in the image, or may be bright spots that have a predetermined luminance value or more among all the bright spots.

[0028] {Feature Calculation Unit 205} The feature amount calculation unit 205 calculates, as a first feature amount, a feature amount indicating a positional relationship between at least two or more bright spots among the bright spots detected by the bright spot detection unit 201. Details of the feature amount calculation process will be described later.

[0029] {Star Identification Department 209} The star identification unit 209 identifies a star corresponding to at least one of the two or more bright points used to calculate the features by the feature calculation unit 205, based on the features calculated by the feature calculation unit 205 and the features stored in the star group feature memory unit 105.

[0030] {Posture estimation unit 213} The attitude estimation unit 213 estimates the attitude of the camera 5 based on the celestial position information of the fixed stars corresponding to each of the at least three or more bright points identified by the fixed star identification unit 209. Details related to the attitude estimation will be described later.

[0031] An example of the functional configuration of the information processing device 10 according to the present disclosure has been described above. Next, details according to the present disclosure will be sequentially described with reference to FIGS.

[0032] <3.Details> <3.1. Calculation of feature values> The feature amount calculation unit 205 calculates a feature amount indicating the positional relationship of at least two or more bright points among the multiple bright points detected by the bright point detection unit 201. Then, the star identification unit 209 compares the feature amount calculated from the image positions of the two or more bright points calculated by the feature amount calculation unit 205 with the feature amount calculated from the celestial position information of two or more stars (star groups) stored in the star group feature amount storage unit 105, and identifies the stars corresponding to each of the two or more bright points based on the comparison result.

[0033] The selection criteria for selecting two or more bright points from the multiple bright points included in the image can be arbitrary, but it is preferable that the selection criteria for the two or more bright points in the feature amount calculation unit 205 and the selection criteria for the two or more fixed stars held as a star group are the same. Hereinafter, with reference to Figures 4A to 4E, an example of the selection criteria for selecting five bright points as an example of at least two or more bright points from the multiple bright points included in the image will be described.

[0034] (Selection of bright spots) {Selection of the first bright spot} Fig. 4A is an explanatory diagram for explaining an example of selection of a first bright spot according to the present disclosure. In Fig. 4A, each circle represents a bright spot. The feature amount calculation unit 205 selects a bright spot that satisfies a predetermined condition as a first bright spot from among the multiple bright spots detected by the bright spot detection unit 201.

[0035] For example, the feature amount calculation unit 205 may select, as the first bright point, a bright point P1 that is closest to the center position in the image I, as shown in Fig. 4A, among all the bright points included in the image I. However, the bright point that is closest to the center position in the image I is an example of a bright point that satisfies the above-mentioned predetermined condition, and the predetermined condition according to the present disclosure is not limited to this example.

[0036] For example, the feature calculation unit 205 may select the bright spot with the highest brightness value among all the bright spots contained in image I as the bright spot that satisfies a specified condition (i.e., the first bright spot), or may select the bright spot that is closest to a specified position in image I as the bright spot that satisfies the specified condition.

[0037] {Selection of the second bright spot} 4B is an explanatory diagram for explaining an example of selection of the second bright point according to the present disclosure. The feature amount calculation unit 205 selects, as the second bright point, the bright point P2 that is closest to the bright point P1, which is the first bright point, among the bright points that are separated by a predetermined value R or more from the bright point P1 in the image I.

[0038] {Selection of the third bright spot} 4C is an explanatory diagram for explaining an example of selection of a third bright point according to the present disclosure. The feature amount calculation unit 205 selects, as the third bright point, a bright point that is next closest to the first bright point after the second bright point among bright points that exist within a predetermined range from the symmetrical direction of the second bright point in the image I starting from the first bright point.

[0039] For example, the symmetrical direction of the second bright point with respect to the first bright point is the direction in which a virtual line extending from the bright point P1 forms an angle of 180 degrees with a line segment connecting the first bright point and the second bright point. In this case, as shown in Fig. 4C, the feature amount calculation unit 205 selects the bright point P3, which is the second closest to the bright point P1 after the bright point P2, from the bright point P1 and included in the range of angles between the bright point P1 and the line segment connecting the bright point P1 and the bright point P2 (i.e., the range on the side where the bright point P2 is not located out of the two ranges partitioned by the dashed line L1), as the third bright point.

[0040] {Selection of the fourth bright spot} 4D is an explanatory diagram for explaining an example of selection of the fourth bright point according to the present disclosure. The feature amount calculation unit 205 selects, as the fourth bright point, the bright point next closest to the third bright point from the first bright point among the bright points existing within a predetermined range from the symmetrical direction of the third bright point in the image I starting from the first bright point.

[0041] For example, the symmetrical direction of the third bright point with respect to the first bright point is the direction in which a virtual line extending from the bright point P1 forms an angle of 180 degrees with a line segment connecting the first bright point and the third bright point. In this case, as shown in Fig. 4D, the feature amount calculation unit 205 selects the bright point P4, which is the second closest to the bright point P1 after the bright point P3, from the bright point P1 and included in the range of angles between the bright point P1 and the line segment connecting the bright point P1 and the bright point P3 (i.e., the range on the side where the bright point P3 is not located out of the two ranges partitioned by the dashed line L2), as the fourth bright point.

[0042] {Selection of the 5th bright spot} 4E is an explanatory diagram for explaining an example of selection of the fifth bright point according to the present disclosure. The feature amount calculation unit 205 selects, as the fifth bright point, the bright point that is the second closest to the first bright point after the fourth bright point among the bright points that exist within a predetermined range from the symmetrical direction of the fourth bright point in the image I starting from the first bright point.

[0043] For example, the symmetrical direction of the fourth bright point with respect to the first bright point is the direction in which a virtual line extending from the bright point P1 forms an angle of 180 degrees with a line segment connecting the first bright point and the fourth bright point. In this case, as shown in Fig. 4E, the feature amount calculation unit 205 selects the bright point P5, which is the second closest to the bright point P1 after the bright point P4, as the fifth bright point from the bright point P1 and which is included in the range of angles between the bright point P1 and the line segment connecting the bright point P1 and the bright point P4 (i.e., the range on the side where the bright point P4 is not located out of the two ranges partitioned by the dashed line L3).

[0044] An example of the selection method for the first bright point to the fifth bright point has been described above. The above-mentioned example of the selection method is a method of selecting bright points located in a dispersed manner in each direction with the first bright point as the center as the second bright point to the fifth bright point. This allows the fixed star identification unit 209 described later to identify the fixed stars corresponding to each of the first bright point to the fifth bright point with higher accuracy. Next, with reference to FIG. 5, the details of the feature amount calculation unit 205 calculating the feature amount using the first bright point to the fifth bright point will be described.

[0045] (Calculation of feature values) 5 is an explanatory diagram for explaining an example of a feature calculated by the feature calculation unit 205. As described above, the feature calculation unit 205 according to the present disclosure calculates a feature indicating a positional relationship between at least two or more bright spots. In the following description, the position of a bright spot in an image may be expressed as an image position.

[0046] For example, the feature amount calculated by the feature amount calculation unit 205 includes a great circle distance based on the image positions of at least two or more bright points when it is assumed that the bright points are fixed stars. Note that, more specifically, the great circle distance in this specification is the central angle of each bright point when the camera 5 is used as the starting point, but for convenience of explanation, it may be simply referred to as the great circle distance in this specification.

[0047] For example, the feature amount calculation unit 205 calculates the great circle distance D1 based on the positions of the bright spots P1 and P2 in the image. The feature amount calculation unit 205 also calculates the great circle distance D2 based on the image positions of the bright spots P1 and P3. The feature amount calculation unit 205 also calculates the great circle distance D3 based on the image positions of the bright spots P1 and P4. Furthermore, the feature amount calculation unit 205 calculates the great circle distance D4 based on the image positions of the bright spots P1 and P5. The feature amount calculation unit 205 may also perform a conversion process by standardization in conjunction with the calculation of the great circle distances D1 to D4, and convert the values ​​of the great circle distances D1 to D4 so that, for example, the maximum value is 1 and the minimum value is 0.

[0048] Furthermore, the feature amount calculation unit 205 may calculate an angle between three or more bright points as a feature amount. For example, the feature amount calculated by the feature amount calculation unit 205 may include an angle between a line segment connecting the first bright point and the second bright point and a line segment connecting the first bright point and the third bright point as an angle between three or more bright points. For example, the angle between three or more bright points may be an angle AD1 between a line segment connecting the bright point P1 and the bright point P2 and a line segment connecting the bright point P1 and the bright point P3 as shown in FIG. 5.

[0049] Furthermore, the feature amount calculated by feature amount calculation unit 205 may include, as the angle between three or more bright spots, an angle between a line segment connecting the first bright spot and the third bright spot and a line segment connecting the first bright spot and the fourth bright spot. For example, the angle between three or more bright spots may be an angle AD2 between a line segment connecting the bright spot P1 and the bright spot P3 and a line segment connecting the bright spot P1 and the bright spot P4, as shown in FIG.

[0050] As described above, when a total of five bright points, the first bright point to the fifth bright point, are selected, the feature amount calculation unit 205 may calculate the great circle distances D1 to D4 and the angles AD1 and AD2 as feature amounts. Then, the star identification unit 209 identifies a star corresponding to at least one of the first bright point to the fifth bright point based on each feature amount calculated by the feature amount calculation unit 205. More specifically, the star identification unit 209 identifies a star corresponding to at least one of the first bright point to the fifth bright point based on each feature amount calculated by the feature amount calculation unit 205 and the feature amount stored in the star group feature amount storage unit 105. Next, an example of a database in which the star group feature amount storage unit 105 stores star groups in association with feature amounts will be described.

[0051] <3.2. Advance preparation> Fig. 6 is an explanatory diagram for explaining an example of a database in which star groups and features are associated and stored by the star group feature storage unit 105. As shown in Fig. 6, the star group feature storage unit 105 stores a number C1 for each star included in each star group, an angle C2 between the star and a great circle distance C3, each associated with the star.

[0052] For example, the HIP number shown in FIG. 3 is input as the number C1. For example, for each star in the column of number N1, the number of the reference star as the first bright point is input. Then, when the selection criteria for the second bright point to the fifth bright point as described above are applied, the star corresponding to the second bright point is input as number N2, the star corresponding to the third bright point is input as number N3, the star corresponding to the fourth bright point is input as number N4, and the star corresponding to the fifth bright point is input as number N5. Therefore, the star group feature storage unit 105 holds the stars corresponding to each of the second bright point to the fifth bright point and each feature as a database when a certain star is the first bright point.

[0053] In addition, just as the feature calculation unit 205 performs a conversion process by standardization in conjunction with the calculation of the great circle distance, the great circle distance C3 held by the star group feature memory unit 105 may also be converted so that the maximum value is 1 and the minimum value is 0, for example.

[0054] Each feature stored in the star group feature storage unit 105 is calculated based on the celestial position information (right ascension and declination) of the stars stored in the star feature storage unit 101. Hereinafter, an example of a method for calculating the feature based on the celestial position information will be described with reference to Figs. 7 and 8.

[0055] Fig. 7 is an explanatory diagram for explaining an example of a method for calculating the great circle distance D1 based on celestial position information. Fig. 7 explains an example of a method for calculating the great circle distance D1 between a star S1 and a star S2 (more precisely, the central angle of an arc connecting the stars S1 and S2).

[0056] The great circle distance D1 between the stars S1 and S2 is calculated using the right ascension RA and declination DE of each of the stars S1 and S2. For example, the right ascension of the star S1 is RA1 and the declination is DE1, and the right ascension of the star S2 is RA2 and the declination is DE2. In this case, the great circle distance D1 between the stars S1 and S2 can be calculated using the following formula (Equation 1).

[0057]

number

[0058] Next, an example of a method for estimating the angle between three stars will be described with reference to FIG.

[0059] Fig. 8 is an explanatory diagram for explaining an example of a method for calculating the angle AD1 based on celestial object position information. Fig. 8 explains an example of a method for calculating the angle AD1 between the line segment connecting the fixed star S1 and the fixed star S2 and the line segment connecting the fixed star S1 and the fixed star S3.

[0060] The angle AD1 is the great circle distance Y11 between the stars S1 and S2, the great circle distance Y12 between the stars S1 and S3, and the great circle distance Y S23 More specifically, the formed angle AD1 is calculated using the following formula (Formula 2).

[0061]

number

[0062] The database held by the star group feature storage unit 105 described above may be prepared in advance on the ground, or may be updated as appropriate depending on the shooting conditions in space.

[0063] Next, the process in which the star identifying unit 209 identifies a star corresponding to a bright spot will be described in detail.

[0064] <3.3. Identifying Stars> The star identification unit 209 identifies a star corresponding to at least one of the five bright points used to calculate the features by the feature calculation unit 205, based on the features calculated by the feature calculation unit 205 and the features stored in the star group feature memory unit 105.

[0065] For example, the star identification unit 209 compares the four great circle distances and two angles calculated from the five bright points by the feature calculation unit 205 with the four great circle distances and two angles for each star group stored in the star group feature storage unit 105. Then, based on the result of the comparison, the star identification unit 209 identifies the star group that includes the stars corresponding to the five bright points, and identifies the stars corresponding to each of the five bright points.

[0066] For example, when disturbances such as noise occur in the camera 5, or when obstacles such as space debris are included in the angle of view, there is a possibility that bright points that should be captured in the image are not captured. In consideration of the influence of such shooting environments, the star identifying unit 209 does not necessarily need to identify stars corresponding to all five bright points. For example, the star identifying unit 209 may identify a star corresponding to at least one of the five bright points.

[0067] The above has described the details of the process in which the star identifying unit 209 identifies a star corresponding to a bright point. Next, the details of the process in which the attitude estimating unit 213 estimates the attitude of the camera 5 will be described.

[0068] <3.4. Posture estimation> The attitude estimation unit 213 estimates the attitude of the camera 5 based on celestial position information of the fixed stars corresponding to each of the at least three or more bright points identified by the fixed star identification unit 209 .

[0069] First, the attitude estimation unit 213 calculates the Xw coordinate, Yw coordinate, and Zw coordinate in the world coordinate system W (Xw, Yw, Zw) of the star identified as the star corresponding to the bright spot using the right ascension RA and declination DE of the star, respectively, according to the following equations (Equation 3) to (Equation 5).

[0070]

number

[0071]

number

[0072]

number

[0073] Then, the attitude estimation unit 213 estimates the world coordinate system W (Xw, Yw, Zw) of the star and the attitude of the camera 5 (R 11 ~R 33 The relationship between the light intensity (u, v) and the image position (u, v) of the bright spot is calculated using the following formula (Formula 6).

[0074]

number

[0075] Then, the attitude estimation unit 213 calculates the relational expression according to the above formula (Formula 6) for each bright point for which a star has been identified by the star identification unit 209.

[0076] Then, the posture estimation unit 213 estimates the posture (R 11 ~R 33At this time, the posture estimation unit 213 estimates the posture (R 11 ~R 33 ) may be estimated. The statistical method may be, for example, the least squares method.

[0077] The details of the present disclosure have been described above. Next, an example of the operation process of the information processing device 10 according to the present disclosure will be described in sequence with reference to FIG.

[0078] <4. Operation processing example> 9 is an explanatory diagram for explaining an example of operation processing of the information processing device 10 according to the present disclosure. First, the control unit 200 acquires an image obtained by photographing the universe with the camera 5 (S101).

[0079] Then, the bright spot detection unit 201 detects a plurality of bright spots from the image acquired by the camera 5 (S105).

[0080] Next, the feature amount calculation unit 205 calculates a feature amount indicating the positional relationship between at least two or more bright spots (S109).

[0081] Next, the star identification unit 209 compares the feature amounts of at least two or more bright points obtained from the image with the feature amounts of each of the multiple star groups stored in the star group feature amount storage unit 105 (S113).

[0082] Then, based on the result of the comparison in S113, the star identifying unit 209 identifies the star corresponding to the bright spot whose feature amount has been calculated by the feature amount calculation unit 205 (S117).

[0083] Then, the attitude estimation unit 213 estimates the attitude of the camera 5 based on the celestial position information of each of the at least three or more stars identified in S117 (S121), and the information processing device 10 according to the present disclosure ends the process.

[0084] The operational processing example according to the present disclosure has been described above. Next, an example of the effects of the present disclosure will be described.

[0085] <5. Examples of effects> According to the present disclosure described above, various operational effects can be obtained. For example, the information processing device 10 according to the present disclosure can specify a star corresponding to a bright point with high accuracy even in a shooting environment where the attitude of the camera 5 may fluctuate by using the great circle distance as a feature amount that is highly robust against the rotation and scale of the camera 5. In addition, the size of the feature amount database stored in the star group feature amount storage unit 105 can be kept to about 500 KB. This makes it possible to realize the functions of the information processing device 10 described above even in a small device such as a microcomputer, thereby making it possible to reduce costs. As a result, for example, the information processing device 10 can be mounted on a small satellite.

[0086] Furthermore, by the feature calculation unit 205 selecting bright points that are distributed in various directions within the image rather than selecting only bright points that are in one area of ​​the image for the second bright point to the fifth bright point, the star identification unit 209 can identify the stars corresponding to each of the first bright point to the fifth bright point with greater accuracy.

[0087] Moreover, the attitude estimation unit 213 according to the present disclosure estimates a relational expression relating to the attitude of the camera 5 and the image position of the bright point based on the celestial position information of the star corresponding to the identified bright point. Then, the attitude estimation unit 213 estimates the attitude of the camera 5 based on the relational expression estimated from each of the three or more bright points identified by the star identification unit 209 and a statistical method such as the least squares method. This allows the attitude estimation unit 213 to uniquely estimate the attitude of the camera 5 without the need to calculate candidate values.

[0088] <6. Hardware configuration example> The above is a description of the embodiment of the present disclosure. The above-described information processing is realized by cooperation between software and hardware of the information processing device 10 described below.

[0089] 10 is a block diagram showing a hardware configuration of an information processing device 10 according to the present disclosure. The information processing device 10 includes a CPU (Central Processing Unit) 1001, a ROM (Read Only Memory) 1002, a RAM (Random Access Memory) 1003, and a host bus 1004. The information processing device 10 also includes a bridge 1005, an external bus 1006, an interface 1007, an input device 1008, an output device 1010, a storage device (HDD) 1011, a drive 1012, and a communication device 1015.

[0090] The CPU 1001 functions as an arithmetic processing device and a control device, and controls the overall operation of the information processing device 30 according to various programs. The CPU 1001 may also be a microprocessor. The ROM 1002 stores programs and arithmetic parameters used by the CPU 1001. The RAM 1003 temporarily stores programs used in the execution of the CPU 1001 and parameters that change appropriately during the execution. These are connected to each other by a host bus 1004 consisting of a CPU bus and the like. The functions of the bright spot detection unit 201, the feature amount calculation unit 205, the star identification unit 209, and the like described with reference to FIG. 2 can be realized by the cooperation of the CPU 1001, the ROM 1002, and the RAM 1003 with software.

[0091] The host bus 1004 is connected to an external bus 1006 such as a PCI (Peripheral Component Interconnect / Interface) bus via a bridge 1005. It is not necessary to configure the host bus 1004, the bridge 1005, and the external bus 1006 separately, and these functions may be implemented in a single bus.

[0092] The input device 1008 is composed of input means for the user to input information, such as a mouse, keyboard, touch panel, button, microphone, switch, and lever, and an input control circuit that generates an input signal based on the user's input and outputs it to the CPU 1001. A user of the information processing device 10 can input various data to the information processing device 10 and instruct the information processing device 10 to perform processing operations by operating the input device 1008.

[0093] The output device 1010 includes, for example, a display device such as a liquid crystal display device, an OLED device, and a lamp. Furthermore, the output device 1010 includes an audio output device such as a speaker and a headphone. The output device 1010 outputs, for example, reproduced content. Specifically, the display device displays various information such as reproduced video data as text or images. Meanwhile, the audio output device converts the reproduced audio data, etc. into audio and outputs it.

[0094] The storage device 1011 is a device for storing data. The storage device 1011 may include a storage medium, a recording device for recording data on the storage medium, a reading device for reading data from the storage medium, and a deleting device for deleting data recorded on the storage medium. The storage device 1011 is configured, for example, with an HDD (Hard Disk Drive). This storage device 1011 drives a hard disk and stores programs executed by the CPU 1001 and various data.

[0095] The drive 1012 is a reader / writer for a storage medium, and is built into or externally attached to the information processing device 10. The drive 1012 reads out information recorded in a removable storage medium 60, such as an attached magnetic disk, optical disk, magneto-optical disk, or semiconductor memory, and outputs the information to the RAM 1003. The drive 1012 can also write information to the removable storage medium 60.

[0096] The communication device 1015 is, for example, a communication interface configured with a communication device for connecting to the network 50. The communication device 1015 may be a wireless LAN compatible communication device, a LTE (Long Term Evolution) compatible communication device, or a wired communication device that performs wired communication.

[0097] The hardware configuration example according to the present disclosure has been described above. Next, supplementary information according to the present disclosure will be described.

[0098] <7. Supplementary Information> Although the preferred embodiment of the present disclosure has been described in detail above with reference to the accompanying drawings, the present disclosure is not limited to such examples. It is clear that a person having ordinary knowledge in the technical field to which the present disclosure belongs can conceive of various modified or amended examples within the scope of the technical ideas described in the claims, and it is understood that these also naturally belong to the technical scope of the present disclosure.

[0099] For example, in the present specification, an example has been described in which the feature amount calculation unit 205 selects five bright points, ie, the first bright point to the fifth bright point, and calculates feature amounts from the five bright points. However, when identifying a star corresponding to a bright point, the feature amount calculation unit 205 does not necessarily need to select five bright points and calculate feature amounts from the five bright points. For example, when identifying a star corresponding to a bright point, at least two or more bright points are required for calculating feature amounts. Also, when estimating the attitude of the camera 5, at least three or more bright points are required for calculating feature amounts. The information processing device 10 according to the present disclosure may appropriately change the number of bright points selected and the number of feature amounts calculated according to the application and the required accuracy.

[0100] Further, in this specification, an example has been described in which the camera 5 and the information processing device 10 are mounted on the artificial satellite 1, but the camera 5 and the information processing device 10 may be mounted on any device on the Earth.

[0101] In addition, the feature amount calculation unit 205 may increase or decrease the number of feature amounts to be calculated depending on how the bright points included in the image are captured. For example, if the bright points included in the image are blurred, the feature amount calculation unit 205 may increase the number of selected bright points and calculate more feature amounts. This allows the star identification unit 209 to identify the star corresponding to the bright point with higher accuracy even if the sensitivity or performance of the camera 5 affects how the bright points are captured.

[0102] In addition, each step in the processing of the information processing device 10 in this specification does not necessarily have to be processed in chronological order according to the order described in the flowchart. For example, each step in the processing of the information processing device 10 may be processed in an order different from the order described in the flowchart or in parallel.

[0103] It is also possible to create a computer program for causing hardware such as a CPU, ROM, and RAM built into the information processing device 10 to perform functions equivalent to those of the above-described components of the information processing device 10. A non-transitory storage medium storing the computer program is also provided.

[0104] In addition, the effects described in this specification are merely descriptive or exemplary and are not limiting. In other words, the technology according to the present disclosure may achieve other effects that are apparent to a person skilled in the art from the description of this specification, in addition to or in place of the above effects.

[0105] Note that the following configurations also fall within the technical scope of the present disclosure. A detection unit that detects a plurality of bright points from an image obtained by the camera photographing space; A calculation unit that calculates a first feature amount indicating a positional relationship of at least two or more bright points among the multiple bright points detected by the detection unit; An identification unit that identifies a star corresponding to at least one of the two or more bright points based on the first feature amount calculated by the calculation unit and a second feature amount including a central angle between each of the stars in an equatorial coordinate system based on celestial position information of at least two or more stars; An information processing device comprising: (2) The calculation unit is calculating the first feature amount based on an image position of a first bright point, which is a bright point that satisfies a predetermined condition among the detected plurality of bright points, and an image position of a second bright point, which is a closest bright point among the bright points that are distant from the image position of the first bright point by a predetermined value or more; The information processing device according to (1). (3) The first feature amount includes the central angle between each of the bright points based on the image positions of the at least two or more bright points when the bright points are assumed to be stars. The information processing device according to (2). (4) The at least two or more bright spots are three or more bright spots, an attitude estimation unit that estimates an attitude of the camera based on the celestial position information of stars corresponding to each of the three or more bright points identified by the identification unit; The information processing device according to (2) or (3), further comprising: (5) The calculation unit is Calculating the first feature amount based on an image position of a third bright point, which is the second closest bright point to the first bright point after the second bright point, among bright points existing within a predetermined range from a symmetrical direction of the second bright point with the first bright point as a starting point, and an image position of the first bright point; The information processing device according to (4). (6) the first feature amount includes an angle between the three or more bright points, The second feature amount includes an angle between the three or more stars based on the central angle of the three or more stars. The information processing device according to (5). (7) The first feature amount includes, as an angle between the three or more bright points, an angle between a line segment connecting the first bright point and the second bright point and an angle between a line segment connecting the first bright point and the third bright point. The information processing device according to (6). (8) The three or more bright points are four or more bright points, The calculation unit is Calculating the first feature amount based on an image position of a fourth bright point, which is the second closest bright point to the first bright point after the third bright point, among bright points existing within a predetermined range from a symmetrical direction of the third bright point, starting from the first bright point; The information processing device according to (7). (9) The first feature amount includes, as an angle between the three or more bright points, an angle between a line segment connecting the first bright point and the third bright point and an angle between a line segment connecting the first bright point and the fourth bright point. The information processing device according to (8). (10) The four or more bright points are five or more bright points, The calculation unit is Calculating the first feature amount based on an image position of a fifth bright point, which is the second closest bright point to the first bright point after the fourth bright point, among bright points existing within a predetermined range from a symmetrical direction of the fourth bright point, starting from the first bright point; The information processing device according to (9). (11) The posture estimation unit is Based on celestial position information of a star corresponding to one bright point identified by the identification unit, estimate a relational expression relating to the attitude of the camera and an image position of the bright point, and estimate the attitude of the camera based on the relational expression and a statistical method estimated from each of the three or more bright points identified by the identification unit. The information processing device according to any one of (4) to (10). (12) Detecting a plurality of bright points from an image obtained by a camera photographing space; Calculating a first feature amount indicating a positional relationship between at least two or more of the detected bright points; Identifying a star corresponding to at least one of the two or more bright points based on the calculated first feature amount and a second feature amount including a central angle between each of the stars in an equatorial coordinate system based on celestial position information of at least two or more stars; 2. An information processing method implemented by a computer, comprising: (13) On the computer, A detection function that detects multiple bright spots from images taken by a camera of space, A calculation function that calculates a first feature amount that indicates a positional relationship of at least two or more bright points among the multiple bright points detected by the detection function; A function for identifying a star corresponding to at least one of the two or more bright points based on the first feature calculated by the calculation function and a second feature including a central angle between each of the stars in an equatorial coordinate system based on celestial position information of at least two or more stars; A program to achieve this. [Explanation of symbols]

[0106] 1 satellite 5. Camera 10. Information processing device 100 Storage section 101 Stellar feature memory unit 105 Star group feature memory unit 200 Control section 201 Bright spot detection unit 205 Feature Calculation Unit 209 Star Identification Department 213 Posture estimation section

Claims

1. A detection unit that detects a plurality of bright points from an image obtained by capturing an image of space with a camera; a calculation unit that calculates a first feature amount indicating a positional relationship of at least two or more bright points among the plurality of bright points detected by the detection unit; an identification unit that identifies a star corresponding to at least one of the two or more bright points based on the first feature amount calculated by the calculation unit and a second feature amount including a central angle between the stars in an equatorial coordinate system based on celestial position information of at least two or more stars; Equipped with The calculation unit is An information processing device that calculates the first feature based on the image position of a first bright point, which is a bright point that satisfies a predetermined condition among the detected multiple bright points, and the image position of a second bright point, which is the closest bright point among the bright points that are further away from the image position of the first bright point by a predetermined value or more.

2. The first feature amount includes the central angle between each of the at least two or more bright points based on image positions of each of the bright points when it is assumed that the bright points are stars. The information processing device according to claim 1 .

3. The at least two or more bright points are three or more bright points, an attitude estimation unit that estimates an attitude of the camera based on the celestial position information of stars corresponding to each of the three or more bright points identified by the identification unit; The information processing device according to claim 2 , further comprising:

4. The calculation unit is Calculating the first feature amount based on an image position of a third bright point, which is the second closest bright point to the first bright point after the second bright point, among bright points existing within a predetermined range from a symmetrical direction of the second bright point with the first bright point as a starting point, and an image position of the first bright point; The information processing device according to claim 3 .

5. the first feature amount includes an angle between the three or more bright points, The second feature amount includes an angle between the three or more stars based on the central angle of the three or more stars. The information processing device according to claim 4.

6. The first feature amount includes, as an angle formed by the three or more bright points, an angle formed by a line segment connecting the first bright point and the second bright point and a line segment connecting the first bright point and the third bright point. The information processing device according to claim 5 .

7. The three or more bright points are four or more bright points, The calculation unit is Calculating the first feature amount based on an image position of a fourth bright point, which is the second closest bright point to the first bright point after the third bright point, among bright points existing within a predetermined range from a symmetrical direction of the third bright point with the first bright point as a starting point, and an image position of the first bright point; The information processing device according to claim 6.

8. The first feature amount includes, as an angle formed by the three or more bright points, an angle formed by a line segment connecting the first bright point and the third bright point and a line segment connecting the first bright point and the fourth bright point. The information processing device according to claim 7.

9. The four or more bright points are five or more bright points, The calculation unit is Calculating the first feature amount based on an image position of a fifth bright point, which is the second closest bright point to the first bright point after the fourth bright point, among bright points existing within a predetermined range from a symmetrical direction of the fourth bright point, starting from the first bright point; The information processing device according to claim 8.

10. The posture estimation unit is Based on celestial position information of a star corresponding to one bright point identified by the identification unit, a relational expression relating to the attitude of the camera and the image position of the bright point is estimated, and based on the relational expression and a statistical method estimated from each of the three or more bright points identified by the identification unit, the attitude of the camera is estimated. The information processing device according to claim 9.

11. Detecting a plurality of bright points from an image obtained by a camera photographing space; calculating a first feature amount indicating a positional relationship between at least two or more of the detected bright points; Identifying a star corresponding to at least one of the two or more bright points based on the calculated first feature amount and a second feature amount including a central angle between each of the stars in an equatorial coordinate system based on celestial position information of at least two or more stars; Including, An information processing method executed by a computer, wherein calculating the first characteristic amount includes calculating the first characteristic amount based on the image position of a first bright point, which is a bright point among the detected plurality of bright points and satisfies a predetermined condition, and the image position of a second bright point, which is the closest bright point among the bright points and is away from the image position of the first bright point by a predetermined value or more.

12. On the computer, A detection function that detects multiple bright spots from images taken by a camera of space, A calculation function that calculates a first feature amount that indicates a positional relationship of at least two or more bright points among the plurality of bright points detected by the detection function; a function for identifying a star corresponding to at least one of the two or more bright points based on the first feature calculated by the calculation function and a second feature including a central angle between the stars in an equatorial coordinate system based on celestial position information of at least two or more stars; Realize this, The calculation function is a program that calculates the first feature based on the image position of a first bright point, which is a bright point that satisfies a predetermined condition among the detected multiple bright points, and the image position of a second bright point, which is the closest bright point among the bright points that are further away from the image position of the first bright point by a predetermined value or more.

Images