JP5747646B2 - Electronic device, data generation method, and data generation program - Google Patents

Description

  The present invention relates to an electronic device, a data generation method, and a data generation program.

Conventionally, a method for detecting the movement of a subject from an input image signal has been disclosed. For example, in Patent Document 1, a setting in which the entire screen area is divided into a predetermined number of detection areas, a luminance threshold value for determining a luminance change, and a luminance change pattern at the time of lighting on / off switching are stored in advance. Selecting a luminance signal for each of the detection regions from the input image signal;
Detecting a luminance signal in the same detection region for each image frame, comparing the luminance signal with the luminance threshold value, and checking the luminance change pattern when the luminance change is detected; The subject motion detection method includes a step of determining whether or not the luminance change pattern is at the time of illumination switching and determining that the subject motion has been detected when it is determined that the brightness change pattern is not at the time of illumination switching.

  On the other hand, a portable information processing device including a motion sensor that detects the movement of the device itself is disclosed. For example, in Patent Document 2, a motion sensor unit, a processing unit that performs predetermined processing on the output of the motion sensor unit, a usage state detection unit that detects a usage state of the portable information processing apparatus by a user, and a usage state are detected. When this is done, there is shown a portable information processing device comprising a control means for stopping at least one of the motion sensor section and the processing means.

JP 2004-193940 A JP 2005-286809 A

  For example, when an electronic device tries to extract another electronic device that is moving in the same manner as the movement of its own electronic device detected by the motion sensor from the image obtained by the image sensor, it is detected by the motion sensor. It is necessary to compare the waveform indicating the movement of the own device with the waveform indicating the movement of the other electronic device in the video and determine whether or not the same movement is performed from these waveforms.

However, since the amplitude of the signal obtained by the motion sensor and the amplitude of the video signal obtained by the image sensor are different in the first place, the electronic apparatus cannot simply compare these waveforms.
As described above, there is a problem that signals obtained from different sensors (for example, a motion sensor and an image sensor) cannot be compared.

  Therefore, the present invention has been made in view of the above problems, and an object of the present invention is to provide an electronic device, a data generation method, and a data generation program that can compare signals obtained from different sensors.

In order to solve the above problems, an electronic device of one embodiment of the present invention includes information indicating the movement of the device itself, and abstraction unit to abstract and information indicating the movement of the other devices, is the abstraction a normalization unit for normalizing the information, the normalized information compared, based on the comparison result, the information indicating the movement of the own device, information and allogeneic showing the movement of the other device And a comparison / determination unit that determines whether or not the information is.

Further, the data generating method according to an embodiment of the present invention normalizes the information indicating the movement of the device itself, and abstraction procedure to abstract and information indicating the movement of another device, the abstracted information a normalization step, the normalized information compared, based on the comparison result, wherein whether the information indicating the movement of the device itself, and information indicating the movement of the other device is a same kind of information A comparison determination procedure.

A data generation program according to an aspect of the present invention includes an abstraction step for abstracting information indicating the motion of the own device and information indicating the motion of another device in a computer , and the abstracted information. a normalization step of normalizing, the normalized information compared, based on the comparison result, wherein the information indicating the movement of the device itself, the information of the other device information and the same type showing the movement of the A data generation program for executing a comparison determination step for determining whether or not there is.

  According to the present invention, signals obtained from different sensors can be compared.

It is a block block diagram of the electronic device in 1st Embodiment. It is a figure for demonstrating the process of the image area extraction part in 1st Embodiment. It is a figure for demonstrating the process of the moving pixel amount calculation part in 1st Embodiment. It is a figure for demonstrating the process of the abstraction part which smoothes the information which shows a motion. It is a figure for demonstrating the process of the abstraction part which smoothes the information which shows the amount of moving pixels. It is the figure where an example of the input data input into an abstraction part and an example of the autocorrelation function calculated from the input data were shown. It is the figure by which an example of the waveform of 1 period average data ave (n) was shown. An example of input data input to the abstraction unit and an example of data obtained by abstracting the input data are shown. It is a figure for demonstrating the process of the normalization part which normalizes the information which shows the abstracted relative distance. It is a figure for demonstrating the process of the normalization part which normalizes the information which shows the abstracted moving pixel amount. It is a figure for demonstrating the process by the comparison determination part. It is the flowchart which showed the flow of the process of the electronic device of 1st Embodiment. It is a schematic diagram of the object specific system of a 2nd embodiment. It is a block block diagram of the 1st electronic device in 2nd Embodiment. It is a block block diagram of the 2nd electronic device in 2nd Embodiment. It is the flowchart which showed the flow of the process of the 2nd electronic device s of 2nd Embodiment.

<First Embodiment>
Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. First, the outline | summary of the electronic device 1 of 1st Embodiment is demonstrated. The electronic device 1 extracts, from the video obtained by the imaging unit 12, another electronic device that is moved in the same movement as the movement of the own device detected in advance by the movement detection unit 11 included in the own device.

  At that time, the electronic device 1 abstracts the information indicating the relative distance of the device itself from the reference position and the information indicating the moving pixel amount of the image area of the other electronic device in the video signal, and the abstracted information Are compared, the two normalized information are compared, and based on the comparison result, it is determined whether or not the two normalized information are the same type of information. Thereby, signals obtained from different sensors (motion detection unit, imaging unit) can be compared.

FIG. 1 is a block configuration diagram of an electronic device 1 according to the first embodiment. The electronic device 1 includes a detection unit 10, a control unit 20, and a communication unit 30.
The detection unit 10 includes a plurality of types of detection units that detect signals indicating the characteristics of the target from the detection target. In the present embodiment, as an example, the detection unit 10 includes a motion detection unit 11 and an imaging unit 12.
The communication unit 30 is configured to be able to communicate with other electronic devices in a wired or wireless manner.

The motion detection unit 11 detects the motion of the device itself, and outputs information indicating the detected motion to the relative distance calculation unit 21. Here, the information indicating the movement is information indicating the movement of the own apparatus in the three-dimensional direction. The motion detection unit 11 includes, for example, a three-dimensional acceleration sensor.
The imaging unit 12 includes, for example, a CCD image sensor and an ADC (AD converter). The imaging unit 12 images another electronic device as a subject at a predetermined frame rate (for example, 30 frames per second) by the CCD image sensor, converts a signal obtained by the imaging into a digital signal by the ADC, and converts the image The digital signal thus output is output to the image region extraction unit 22.

The control unit 20 includes a relative distance calculation unit 21, an image region extraction unit 22, a moving pixel amount calculation unit 23, an abstraction unit 24, a normalization unit 25, a storage unit 26, and a comparison determination unit 27. Prepare.
The relative distance calculation unit 21 calculates the relative distance of the own device based on the position of the own device at a predetermined time for each time from the information indicating the motion input from the motion detection unit 11. Then, the relative distance calculation unit 21 outputs information indicating the relative distance of the own device to the abstraction unit 24.

  The image area extraction unit 22 uses the digital signal obtained by the imaging unit 12 to extract the image area of another electronic device that is the subject from the video imaged at the predetermined frame rate obtained by the imaging unit 12. To do.

  FIG. 2 is a diagram for explaining the processing of the image region extraction unit 22 in the first embodiment. In the drawing, an example of an image of a kth frame (k is a positive integer) before an image area (object) is extracted is shown on the left side. In the image of the kth frame, image areas 41 to 45 of five electronic devices are shown.

  On the right side of the figure, on the right side are vectors ([X1, Y1], [X2, respectively] having coordinates constituting the image regions 41 to 45 of the electronic device extracted by the processing of the image region extraction unit 22 as elements. Y2], [X3, Y3], [X4, Y4], [X5, Y5]).

Here, the storage unit 26 stores in advance reference image data obtained by capturing an image of the electronic device 1 referred to by template matching.
For example, the image region extraction unit 22 reads reference image data obtained by capturing an image of the electronic device 1 that is referred to by template matching from the storage unit 26. The image area extraction unit 22 extracts data of an image area of a predetermined size from the input k-th frame image data, and the extracted image data (for example, data of the image areas 41 to 45 in FIG. 2) and Template matching with the read reference image data is performed.

  Specifically, for example, the image area extraction unit 22 converts the extracted image area data and the read reference image data into blocks of a predetermined number of rows and a predetermined number of columns (for example, 3 × 3), respectively. To divide. Then, for each divided block, the image area extraction unit 22 calculates an absolute value of a difference in luminance values of RGB (red, green, blue) between the extracted image area data and the read reference image data. And the sum of the absolute values of the differences is calculated. The image region extraction unit 22 calculates the sum of absolute values of the differences in all the divided blocks, and calculates the sum of the sums of the absolute values.

Then, when the total sum of the calculated absolute values is smaller than a predetermined threshold, the image area extraction unit 22 extracts the extracted image area data as the image area of the electronic device.
The image area extraction unit 22 performs this process on the entire image while shifting a predetermined pixel. Thereby, the image region extraction unit 22 can extract the image region of the subject from the image of each frame in which the subject (in this case, the electronic device) is captured.
The image area extraction unit 22 outputs information indicating the pixel position of the extracted image area of the subject to the moving pixel amount calculation unit 23.

  The moving pixel amount calculation unit 23 calculates, as the moving pixel amount, a pixel interval from the pixel position of each extracted image region in each image region in a predetermined frame. Specifically, for example, the moving pixel amount calculation unit 23 extracts the pixel position of the center of gravity for each image region extracted by the image region extraction unit 22 from each frame. Then, the moving pixel amount calculation unit 23 calculates a moving pixel amount indicating how far the pixel position of the center of gravity in each frame is away from the pixel position of the center of gravity as a reference with respect to the pixel position of the center of gravity in the predetermined frame. calculate. The moving pixel amount calculation unit 23 outputs information indicating the calculated moving pixel amount to the abstraction unit 24.

FIG. 3 is a diagram for explaining the processing of the moving pixel amount calculation unit 23 in the first embodiment. In the figure, on the left side, an image of the (k−1) th frame, an image of the kth frame, and an image of the (k + 1) th frame are shown from the top.
In the image of the (k−1) th frame, an image area 51 of the electronic device and a reference pixel position 54 that is a pixel position at the center of gravity of the image area 51 of the electronic device are shown.
Similarly, the image area 52 of the electronic device is shown in the image of the k-th frame, and the image area 53 of the electronic device is shown in the image of the k + 1-th frame.

  In the figure, the moving pixel amount 0 in the (k−1) th frame from the top, the moving pixel amount 250 in the kth frame, and the moving pixel amount 500 in the (k + 1) th frame are shown on the right side. .

In the figure, as an example, the moving pixel amount calculation unit 23 receives information indicating the pixel position of the image region 51 of the electronic device in the image of the (k−1) th frame, and the pixel at the center of gravity of the image region 51 of the electronic device. A reference pixel position 54 that is a position is calculated, and a moving pixel amount 0 is calculated.
Similarly, as an example, the moving pixel amount calculation unit 23 receives information indicating the pixel position of the image area 52 of the electronic device in the image of the k-th frame, and calculates the pixel position of the center of gravity of the image area 52 of the electronic device. Then, the number of pixels in which the pixel position of the center of gravity is far from the reference pixel position 54 is calculated as a moving pixel amount (here, 250 as an example).

  Similarly, as an example, the moving pixel amount calculation unit 23 receives information indicating the pixel position of the image area 53 of the electronic device in the image of the (k + 1) th frame, and calculates the pixel position of the center of gravity of the image area 53 of the electronic device. Then, the number of pixels in which the pixel position of the center of gravity is separated from the reference pixel position 54 is calculated as a moving pixel amount (here, 500 as an example).

  Returning to FIG. 1, the abstraction unit 24 abstracts the input information. Specifically, the abstraction unit 24 abstracts information based on signals detected by a plurality of types of detection units. First, an outline of processing of the abstraction unit 24 will be described.

  An example of processing performed by the abstraction unit 24 will be described with reference to FIG. FIG. 4 is a diagram for explaining processing of the abstraction unit 24 that smoothes information indicating motion. On the left side of the figure, as the information indicating the movement, a curve 61 is shown in which the relative distance of the own device at each time is smoothly connected with the position of the own device in a certain frame as a reference position. A curve 62 obtained by smoothing the curve 61 by the abstraction unit 24 is shown on the right side of the figure.

  The abstraction unit 24 abstracts information indicating the relative distance of the own device input from the relative distance calculation unit 21. Specifically, for example, the abstraction unit 24 calculates an autocorrelation function of data in which information indicating the relative distance of the own device is arranged in time series, and based on the calculated autocorrelation function, Abstract the information indicating the relative distance. The abstraction unit 24 outputs information indicating the abstracted relative distance to the normalization unit 25. Details of the processing will be described later.

  An example of processing performed by the abstraction unit 24 will be described with reference to FIG. FIG. 5 is a diagram for explaining the processing of the abstraction unit 24 that smoothes the information indicating the moving pixel amount. On the left side of the figure, as the information indicating the moving pixel amount, a curve 71 in which the moving pixel amount for each time is smoothly connected is shown. A curve 72 obtained by abstracting the curve 71 by the abstraction unit 24 is shown on the right side of FIG.

  The abstraction unit 24 abstracts the moving pixel amount input from the moving pixel amount calculation unit 23. Specifically, for example, the abstraction unit 24 calculates an autocorrelation function of data in which the moving pixel amounts of the electronic device that is the subject are arranged in chronological order, and based on the calculated autocorrelation function, the moving pixel Abstract information indicating quantity. Then, the abstraction unit 24 outputs information indicating the abstracted moving pixel amount to the normalization unit 25.

  Next, details of the processing of the abstraction unit 24 will be described. First, a method for calculating the autocorrelation function calculated by the abstraction unit 24 will be described. FIG. 6 is a diagram illustrating the input data input to the abstraction unit 24 and the autocorrelation function calculated by the abstraction unit 24. FIG. 6A shows a broken line 81 to which input data input to the abstraction unit 24 is connected. Here, the vertical axis represents amplitude, and the horizontal axis represents the number of samples.

  FIG. 6B shows an example of a polygonal line 82 indicating the autocorrelation function calculated by the abstraction unit 24. Here, the vertical axis represents the value of the autocorrelation function, and the horizontal axis represents the number of samples. Further, it is shown that the peak 83 which is the maximum value of the autocorrelation function and the period from the first sample to the sample of the peak 83 are one period τ.

  For example, input data A composed of n terms input to the abstraction unit 24 shown in FIG. 6A is expressed by the following equation (1).

  An array A ′ of m terms (m = n / 2), which is a part of the array of input data A shown in FIG. 6A, is expressed by the following equation (2) (n is 2 The above even numbers, m is a positive integer).

  Here, A ′ is fixed. An array B of m terms obtained by shifting the array of input data A shown in FIG. 6A by t (0 ≦ t ≦ n / 2) is expressed by the following equation (3).

  Here, B is variable.

  The abstraction unit 24 calculates the autocorrelation function based on the array A ′ and the array B obtained by the shift width t according to the following equation (4).

The value becomes closer to 1 as the waveforms of the elements of the arrays A ′ and B that are drawn at predetermined intervals are more similar.
The abstraction unit 24 extracts the data (peak value) of the upwardly convex vertex on the autocorrelation function R (t). Then, when the extracted peak value exceeds a predetermined threshold, the abstraction unit 24 extracts a sample number (or time) that takes the peak value. The abstraction unit 24 extracts the interval (or time interval) between the sample numbers taking the peak values as the period τ.

  The abstraction unit 24 divides the input data A every period by the period τ obtained by the autocorrelation function. If the number of repetitions is num, the abstraction unit 24 calculates the one-cycle average data ave (n) according to the following equation (5).

  FIG. 7 is a diagram showing an example of the waveform of the one-cycle average data ave (n) and the average for every four samples. FIG. 7A shows a waveform 84 of one-cycle average data ave (n). FIG. 7B shows a line 85 in which values obtained by averaging the one-cycle average data ave (n) every four samples are connected.

  FIG. 8 shows an example of input data input to the abstraction unit 24 and an example of data obtained by abstracting the input data. In the figure, a broken line 81 to which input data is connected and a broken line 86 to which data obtained by abstracting the input data are connected are shown. The broken line 86 is a broken line that is connected by the number of periods of the input data A, with the line 85 connected to the average value of the one period average data ave (n) every four samples being used as data for one period.

The abstraction unit 24 delimits the one-cycle average data ave (n) by a predetermined number of divisions (for example, 4), and calculates an average value of the delimited range. Then, the abstraction unit 24 generates data as abstracted data by the number of periods of the input data, with the calculated range of data as one period of data. The abstraction unit 24 then outputs the abstracted data to the normalization unit 25.
As a result, the abstraction unit 24 can generate abstracted data obtained by extracting a large change from the input data, so that the electronic apparatus 1 can compare data obtained by the same type of device. it can.

  In the present embodiment, the abstraction unit 24 performs the abstraction using the value of the autocorrelation function. However, the present invention is not limited to this, and the abstraction unit 24 may perform the abstraction by applying a low-pass filter.

  The normalizing unit 25 normalizes the information indicating the abstracted relative distance input from the abstracting unit 24 and stores the information indicating the normalized relative distance (normalized relative distance) in the storage unit 26. Specifically, for example, the normalization unit 25 normalizes the abstracted relative distance at each time to obtain a value from −1 to 1.

  The process will be described with reference to FIG. FIG. 9 is a diagram for explaining processing of the normalization unit 25 that normalizes information indicating the abstracted relative distance. On the left side of the figure, a curve 62 is shown in which the smoothed relative distances at each time are smoothly connected. On the right side of the figure, a curve 63 in which the normalized relative distances at each time are smoothly connected by the normalizing unit 25 is shown.

  The normalization unit 25 normalizes information indicating the abstracted moving pixel amount input from the abstraction unit 24. Specifically, for example, the normalization unit 25 normalizes the abstracted moving pixel amount at each time to obtain a value from −1 to 1.

  The process will be described with reference to FIG. FIG. 10 is a diagram for explaining the processing of the normalization unit 25 that normalizes information indicating the abstracted moving pixel amount. On the left side of the figure, a curved line 72 in which smoothed moving pixel amounts at each time are smoothly connected is shown. On the right side of the figure, a curve 73 in which the normalized moving pixel amount at each time is smoothly connected by the normalizing unit 25 is shown.

The normalization unit 25 outputs information indicating the normalized moving pixel amount (normalized moving pixel amount) to the comparison determination unit 27.
As described above, the normalization unit 25 normalizes the abstracted data, so that the electronic apparatus 1 can compare data obtained by different types of devices.

  Returning to FIG. 1, the comparison / determination unit 27 reads information indicating the normalized relative distance Nm from the storage unit 26. Then, the comparison / determination unit 27 identifies an image region that has the same type of motion as the motion detected by the motion detection unit 11 based on the normalized relative distance Nd and the normalized moving pixel amount Nm.

  FIG. 11 is a diagram for explaining processing by the comparison determination unit 27. A curve 63 indicating the normalized relative distance at each time and a curve 73 indicating the normalized moving pixel amount at each time are shown. For example, the comparison determination unit 27 calculates the absolute value of the difference between the normalized relative distance at each time and the normalized moving pixel amount at each time, and calculates the sum of the calculated absolute values of the differences at each time. Then, when the sum of the absolute values of the differences is equal to or less than a predetermined threshold, the comparison determination unit 27 uses the same type of motion as the motion detected by the motion detection unit 11 for the image region in which the normalized moving pixel amount is calculated. It is determined that the image area is being processed. The comparison determination unit 27 outputs information indicating the determination result to the outside of the own device.

  In the present embodiment, the comparison / determination unit 27 compares the normalized relative distance Nd with the normalized moving pixel amount Nm. However, the comparison / determination unit 27 does not limit the normalized information to 2 Two or more may be compared, and based on the comparison result, it may be determined whether the two or more normalized information is the same type of information.

  FIG. 12 is a flowchart illustrating a processing flow of the electronic device 1 according to the first embodiment. First, the motion detection unit 11 detects the motion of its own device (step S101). Next, the relative distance calculation unit 21 calculates information indicating the relative distance (step S102). Next, the abstraction unit 24 abstracts information indicating the relative distance (step S103).

Next, the normalization unit 25 normalizes information indicating the abstracted relative distance (step S104). Next, the normalization unit 25 stores information indicating the relative distance obtained by normalization in the storage unit 26 (step S105).
Next, the imaging unit 12 captures a plurality of electronic devices shaken by the user by a predetermined number of frames so as to be included in one image (step S106). Next, the image area extraction unit 22 extracts image areas in which a plurality of electronic devices are captured in all frames (step S107).

  Next, the moving pixel amount calculation unit 23 calculates the moving pixel amount of the image area of one electronic device (step S108). Next, the abstraction unit 24 abstracts the moving pixel amount of the image area of one electronic device (step S109). Next, the normalization unit 25 normalizes the abstracted moving pixel amount (step S110). Next, the comparison determination unit 27 reads information indicating the normalized relative distance from the storage unit 26 (step S111).

Next, the comparison / determination unit 27 determines whether or not the sum of the absolute values of the differences between the normalized relative distance and the normalized moving pixel amount is equal to or less than a threshold (step S112). If the sum of the absolute values of the differences is equal to or less than the threshold (YES in step S112), the comparison determination unit 27 determines that the one electronic device is moving in the same type as the movement detected by the movement detection unit 11. (Step S113).
On the other hand, when the sum of the absolute values of the differences exceeds the threshold (NO in step S112), the comparison determination unit 27 indicates that one electronic device moves differently from the movement detected by the movement detection unit 11. Determination is made (step S114).

  Next, the electronic device 1 determines whether or not the above determination has been made for all image regions in which other electronic devices have been imaged (step S114). If the above determination has not been made for all image regions in which other electronic devices have been imaged (NO in step S114), the electronic device 1 returns to the processing in step S108. On the other hand, when the above determination is made in all image regions where other electronic devices have been imaged (YES in step S114), the electronic device 1 ends the process.

As described above, the electronic device 1 abstracts the relative distance of its own device and normalizes the normalized relative distance, and the normalized moving pixel amount that abstracts and normalizes the moving pixel amount of another electronic device obtained by imaging. Compare
Thereby, the electronic device 1 can compare information detected by different sensors by abstracting and normalizing information detected by different sensors.

  In the present embodiment, the electronic apparatus 1 normalizes the abstracted information after abstracting the information. However, the present invention is not limited to this, and the information may be abstracted after normalizing the information.

<Second Embodiment>
Next, the second embodiment will be described. In the first embodiment described above, the electronic apparatus 1 compares the information sequentially detected by the two types of detection units included in the own apparatus, thereby performing the same kind of movement as the movement of the own apparatus in the past. I identified other electronic devices in the video. In the second embodiment, while the first electronic device 2_1 is being moved by the user, the second electronic device 2_2 performs the same kind of movement as the movement of the first electronic device 2_1. Identify other electronic devices in real time from the video.

  FIG. 13 is a schematic diagram of the target identification system 2 according to the second embodiment. The target identification system 2 includes a first electronic device 2_1 and a second electronic device 2_2. In the same figure, the direction in which the first electronic device 2_1 is swung by the user is shown. The first electronic device 2_1 wirelessly transmits information indicating the normalized relative distance Nd to the second electronic device 2_2 while being shaken by the user.

  FIG. 14 is a block configuration diagram of the first electronic device 2_1 in the second embodiment. Elements common to those in FIG. 1 are denoted by the same reference numerals, and detailed description thereof is omitted. The configuration of the electronic device 2_1 in FIG. 14 is different from the configuration of the electronic device 1 in FIG. 1 in that the detection unit 10 is changed to the detection unit 10b, the control unit 20 is changed to the control unit 20b, and the communication unit 30 is the communication unit. It has been changed to 30b.

The detection unit 10 b includes a motion detection unit 11. The motion detection unit 11 detects the motion of its own device, as in the first embodiment.
The control unit 20b includes a relative distance calculation unit 21, an abstraction unit 24, and a normalization unit 24b.
The normalizing unit 24b outputs information indicating the normalized relative distance Nd to the communication unit 30b based on the movement of the own device.
The communication unit 30b encodes information indicating the normalized relative distance Nd input from the normalization unit 24b, and wirelessly transmits the information indicating the encoded normalized relative distance Nd to the second electronic device 2_2.

  FIG. 15 is a block configuration diagram of the second electronic device 2_2 in the second embodiment. Elements common to those in FIG. 1 are denoted by the same reference numerals, and detailed description thereof is omitted. The configuration of the electronic device 2_2 in FIG. 15 is different from the configuration of the electronic device 1 in FIG. 1 in that the detection unit 10 is changed to the detection unit 10c, the control unit 20 is changed to the control unit 20c, and the storage unit 26 is the storage unit. The communication unit 30 is changed to the communication unit 30c.

The detection unit 10 b includes an imaging unit 12. The imaging unit 12 images a subject as in the first embodiment.
The communication unit 30c receives the encoded normalized relative distance Nd transmitted from the first electronic device 2_1, decodes the received encoded normalized relative distance Nd, and decodes the normalized normalized relative distance Nd. Is stored in the storage unit 26c.

  FIG. 16 is a flowchart illustrating a processing flow of the second electronic device 2_2 of the second embodiment. First, the communication unit 30c receives information indicating the encoded normalized relative distance Nd from the first electronic device 2_1 (step S201). Since the processing from step S202 to step S207 is the same as the processing from step S106 to step S111 in FIG. 12, the description thereof is omitted.

  Next, in step S208, the comparison determination unit 27 determines whether the sum of absolute values of differences between the normalized relative distance and the normalized moving pixel amount is equal to or less than a threshold value. When the sum of the absolute values of the differences between the normalized relative distance and the normalized moving pixel amount is equal to or smaller than the threshold (YES in step S208), the comparison determination unit 27 detects the extracted image area of the electronic device by the electronic device 2_1. It is determined that the same type of movement is performed (step S209). On the other hand, when the sum of the absolute values of the differences between the normalized relative distance and the normalized moving pixel amount exceeds the threshold (NO in step S208), the comparison determination unit 27 determines that the extracted image area of the electronic device is the electronic device 2_1. It is determined that the type of movement is different from the detected movement (step S210).

  Next, the electronic device 2_2 determines whether or not the above determination has been made for all image regions in which other electronic devices have been imaged (step S211). If the above determination has not been made in all image regions in which other electronic devices have been imaged (NO in step S211), the electronic device 2_2 returns to the process in step S204. On the other hand, when the above determination is made in all image regions where other electronic devices have been imaged (YES in step S211), the electronic device 2_2 ends the process.

As described above, in the second embodiment, the first electronic device 2_1 shaken by the user detects the motion of the own device by the motion detection unit 11 included in the own device, and the normalized relative distance based on the motion of the own device. Information indicating Nd is wirelessly transmitted to the second electronic device 2_2.
Then, the second electronic device 2_2 acquires the image of the other electronic device by the imaging unit 12 included in the own device, the normalized moving pixel amount calculated from the image area of the other electronic device, and the first electronic device The normalized relative distance Nd received from the device 2_1 is compared.

  As a result, the second electronic device 2_2 performs real-time monitoring of other electronic devices that are moving in the same type as the movement of the first electronic device 2_1 while the first electronic device 2_1 is being moved. Can be specified.

  Further, by recording a program for executing each process of the electronic device 1 of the present embodiment on a computer-readable recording medium, causing the computer system to read and execute the program recorded on the recording medium, You may perform the various process which concerns on the electronic device 1 mentioned above.

  Here, the “computer system” may include an OS and hardware such as peripheral devices. Further, the “computer system” includes a homepage providing environment (or display environment) if a WWW system is used. The “computer-readable recording medium” means a flexible disk, a magneto-optical disk, a ROM, a writable nonvolatile memory such as a flash memory, a portable medium such as a CD-ROM, a hard disk built in a computer system, etc. This is a storage device.

    Further, the “computer-readable recording medium” refers to a volatile memory (for example, DRAM (Dynamic) in a computer system serving as a server or a client when a program is transmitted via a network such as the Internet or a communication line such as a telephone line. Random Access Memory)) that holds a program for a certain period of time is also included. The program may be transmitted from a computer system storing the program in a storage device or the like to another computer system via a transmission medium or by a transmission wave in the transmission medium. Here, the “transmission medium” for transmitting the program refers to a medium having a function of transmitting information, such as a network (communication network) such as the Internet or a communication line (communication line) such as a telephone line. The program may be for realizing a part of the functions described above. Furthermore, what can implement | achieve the function mentioned above in combination with the program already recorded on the computer system, and what is called a difference file (difference program) may be sufficient.

  As mentioned above, although embodiment of this invention was explained in full detail with reference to drawings, the concrete structure is not restricted to this embodiment, The design etc. of the range which does not deviate from the summary of this invention are included.

DESCRIPTION OF SYMBOLS 1 Electronic device 2 Target identification system 2_1 1st electronic device 2_2 2nd electronic device 10, 10b, 10c Detection part 11 Motion detection part 12 Imaging part 20, 20b, 20c Control part 21 Relative distance calculation part
22 Image region extraction unit 23 Moving pixel amount calculation unit
24, 24b Abstraction unit 25 Normalization unit 26, 26c Storage unit 27 Comparison determination unit 30, 30b, 30c Communication unit

Claims (6)

Information indicating the movement of the device itself, and abstraction unit to abstract and information indicating the movement of the other device,
A normalization unit for normalizing the abstracted information;
The normalized information compared, based on the comparison result, the own device and information indicating the movement of said other device and information indicating the motion determines the comparison determination whether or not the information of the same type of And
An electronic device comprising: Provided with a plurality of types of detection units that detect the movement of its own device and the movement of other devices ,
The abstraction unit, the respectively detected by the plurality of types of detector, and the information indicating the movement of the self-device, to claim 1, wherein the abstracting and information indicating the movement of the other device The electronic device described. Wherein the detection unit is provided with an imaging unit, a motion detector for detecting motion of the apparatus,
A relative distance calculation unit that calculates the relative distance of the own device based on the position of the own device at a predetermined time from information indicating the movement of the own device detected by the motion detection unit;
An image region extraction unit that extracts an image region of another device from the video obtained by the imaging unit;
A moving pixel amount calculation unit that calculates a moving pixel amount in which each of the extracted image regions has moved with reference to the image region in a predetermined frame;
With
The abstraction unit abstracts relative the calculated distance and a moving pixel amount the calculated,
The normalization unit, the relative distances the abstract, and the abstracted moved pixel amount normalized,
The comparison / determination unit identifies an image region having the same type of motion as the motion detected by the motion detection unit, based on the normalized relative distance and the normalized moving pixel amount.
The electronic device according to claim 2, wherein the this. Information the abstraction unit, on the basis of the autocorrelation function number information indicating the motion information and the other device indicating movement of the apparatus, showing the information indicating the movement of the own device, the movement of the other device And abstract
Electronic device according to any one of claims 3 and this claim, wherein. Information indicating the movement of the device itself, and abstraction procedure to abstract and information indicating the movement of the other device,
A normalization procedure for normalizing the abstracted information;
The normalized information compared, based on the comparison result, the own device and information indicating the movement of said other device and information indicating the motion determines the comparison determination whether or not the information of the same type of Procedure and
A data generation method characterized by comprising: On the computer,
Information indicating the movement of the device itself, and abstraction step to abstract and information indicating the movement of the other device,
A normalization step of normalizing the abstracted information;
The normalized information compared, based on the comparison result, the own device and information indicating the movement of said other device and information indicating the motion determines the comparison determination whether or not the information of the same type of Steps,
Data generation program for executing

Images