JP2020188860A - Mountain climber support device, system, method and program - Google Patents

Abstract

To provide proper support information to a mountain climber.SOLUTION: A mountain climber support device comprises: image acquisition means for acquiring an image from a tracker for imaging an image of a mountain climber by tracking the mountain climber; analysis means for analyzing the image for acquiring state information of the mountain climber including at least one of a fatigue degree and a skill level of the mountain climber; and support means for providing support information for supporting mountain climbing to the mountain climber on the basis of the state information of the mountain climber. For example, a recommended mountain climbing route according to a state of the mountain climber and a predicted arrival time to a destination, can be provided as the support information.SELECTED DRAWING: Figure 2

Description

The present invention relates to assistive technology for mountaineers.

The number of victims is increasing with the increase in the mountaineering population in recent years. Therefore, it is required to support climbers to ensure their safety.

Patent Document 1 is mentioned as a technique for assisting a user by using a drone. Patent Document 1 supports the user's sense of sight, hearing, and smell by using an aerial drone and a land drone. Patent Document 1 discloses, for example, observing a route to inform a user of the existence of a dangerous portion.

However, the risk of distress in mountaineering is not determined only by the mountaineering route, but depends on the skill level and fatigue level of the mountaineer. That is, even if the same climbing route is used, it may be safe for a highly skilled climber but dangerous for a less skilled climber, and even if the skill level is the same, the climber's It may be safe if the degree of fatigue is low, but dangerous if the degree of fatigue is high.

As described above, in Patent Document 1, appropriate support cannot be achieved for each user.

Further, Patent Document 2 is mentioned as a technique for detecting a user's physical condition from an image. Patent Document 2 acquires a user's walking characteristics using an image including depth, and detects a physical condition based on the characteristic change. For example, an increase in the degree of fatigue is detected when a decrease in stride length or a decrease in the degree of toe rise occurs.

Special Table 2018-522302 JP-A-2017-205134

The present invention has been made in view of the above circumstances, and an object of the present invention is to provide more appropriate support information to a mountaineer.

In order to achieve the above object, the present invention adopts the following configuration.

The first aspect of the present invention is an image acquisition means for acquiring an image from a tracking device that tracks a mountaineer and captures an image of the mountaineer, and an image acquisition means that analyzes the image to determine the degree of fatigue and skill of the mountaineer. An analysis means for acquiring the state information of the climber including at least one of the degrees, and a support means for providing the climber with support information for supporting the mountain climbing based on the state information of the climber. It is a mountaineer support device equipped with.

In this way, since the support information is provided based on the state information including the degree of fatigue or skill of the climber, it is possible to realize appropriate support according to the situation.

A second aspect of the present invention is a mountaineer support system including the above-mentioned mountaineer support device and a tracking device that tracks the mountaineer and captures an image of the mountaineer.

A third aspect of the present invention is a method for supporting a mountaineer executed by a computer, which includes an image acquisition step of acquiring the image from a tracking device that tracks the mountaineer and captures an image of the mountaineer, and the image. Supporting the mountaineer to climb based on the analysis step of analyzing and acquiring the state information of the mountaineer including at least one of the fatigue level and the skill level of the mountaineer and the state information of the mountaineer. It is a climber support method, including a support step that provides support information for doing so.

The present invention may be regarded as a mountaineer support device or a mountaineer support system having at least a part of the above means. Further, the present invention may be regarded as a mountaineer support method including at least a part of the above processing. Further, the present invention can be regarded as a program for realizing such a method by a computer or a non-temporary recording medium in which the program is recorded. The present invention can be constructed by combining each of the above means and treatments with each other as much as possible.

According to the present invention, appropriate support can be realized according to the condition of the climber.

FIG. 1 is a diagram showing an application example of a mountaineer support system according to the present invention. FIG. 2 is a diagram showing a configuration of a mountaineer support system including a mountaineer support device (information terminal). FIG. 3 is a flowchart of the entire process carried out by the mountaineer support device (information terminal). FIG. 4 is a diagram illustrating a fatigue degree estimation process. FIG. 5 is a diagram illustrating a skill level estimation process. FIG. 6 is a flowchart showing a process of determining a recommended mountain climbing route, which is an example of support information. FIG. 7 is a flowchart showing a process of determining an estimated arrival time, which is an example of support information. FIG. 8 is a diagram for explaining the calculation process of the estimated arrival time.

<Application example>
An application example of the mountaineer support system according to the present invention will be described with reference to FIG. The climber support system 1 includes an air drone 100 and an information terminal 200.

The aviation drone (tracking device) 100 is an autonomously movable flying object that tracks the climber 10 and takes an image of the climber 10. The aviation drone 100 is equipped with a camera (imaging means) and a moving device so that the mountaineer 10 can be photographed from the front facing the mountaineer 10 and the shooting distance and the shooting angle (elevation angle) are constant. Autonomously move to track the climber 10.

The information terminal (climber support device) 200 analyzes an image obtained from the aviation drone 100, calculates a state including the fatigue level and skill level of the mountaineer 10, and provides support according to the state of the mountaineer 10. .. For example, the information terminal 200 recommends a mountaineering route with a difficulty level corresponding to a score according to the fatigue level and skill level of the mountaineer 10, or warns when trying to proceed with a mountaineering route that is too difficult. Or something. Further, the information terminal 200 calculates and provides an estimated arrival time to the destination.

The information terminal 200 detects the posture (skeleton point position) of the climber 10 from the image, grasps the walking motion, and calculates the degree of fatigue from the characteristics of the walking motion. Examples of characteristics of walking motion include the degree of toe elevation, change in the center of gravity of the upper body, the number of steps or stride length, and posture collapse. Fatigue may also be calculated based on face orientation, pulse rate, facial expression, heart rate and the like. The orientation of the face, the pulse rate, the facial expression, the heart rate, and the like can be obtained from the face image of the climber 10. The skill level is calculated from the number of steps or stride length obtained from the image, the frequency of posture collapse, the rate of increase in the degree of fatigue, and the information input in advance (years of mountaineering experience, number of times, equipment).

In this way, the mountaineer support system 1 calculates a state including the fatigue level and skill level of the mountaineer 10 from the image obtained from the aviation drone, and provides appropriate support information according to the state of the mountaineer 10. Can be done.

<Climber support system>
[Constitution]
An embodiment of the present invention will be described with reference to FIG. FIG. 2 is a block diagram showing a configuration of a mountaineer support system 1 according to an embodiment of the present invention. The mountaineer support system 1 generally includes an air drone 100 (tracking device) and an information terminal 200 (climber support device).

The aviation drone 100 includes a camera 102, a flight control unit 104, and an image transmission unit 106. The camera 102 periodically captures an image. The image data captured by the camera 102 may be either a monochrome image or a color image, and the resolution, frame rate, and format of the image data are also arbitrary. The flight control unit 104 autonomously controls the flight (movement) of the air drone 100. For example, the flight control unit 104 autonomously controls the flight so that the camera 102 can photograph the climber 10 from the front and the shooting distance and the shooting angle (elevation angle) are constant. If necessary, the flight control unit 104 may interrupt the tracking of the mountaineer 10 and control the air drone 100 so as to proceed along the mountaineering route and observe the state of the mountaineering route. The image transmission unit 106 transmits the image data captured by the camera 102 to the information terminal 200 by wireless communication. Data other than image data may be exchanged between the aviation drone 100 and the information terminal 200.

The information terminal 200 of the present embodiment is a computer including a microprocessor, a memory, an output unit (display, speaker), an input unit (touch panel, buttons), and a communication unit. When the microprocessor executes the program stored in the memory, the information terminal 200 has an image acquisition unit 202, a human body detection unit 204, a face image / facial expression acquisition unit 206, a posture estimation unit 208, a fatigue degree estimation unit 212, and a skilled person. It functions as a degree estimation unit 214, a recommended route determination unit 216, an estimated time estimation unit 218, a mountain climbing route database 220, and an information providing unit 222.

[processing]
FIG. 3 is a flowchart showing a process performed by the information terminal 200 in the present embodiment. The function of the information terminal 200 will be described with reference to FIG.

In step S11, the image acquisition unit 202 acquires the image data taken by the aviation drone 100. As described above, the aviation drone 100 tracks the climber 10 and shoots the climber 10 from the front at a substantially constant shooting distance and shooting angle. Therefore, the image data taken by the aviation drone 100 includes the whole body including the face of the climber 10. The image acquisition unit 202 provides the acquired image data to the human body detection unit 204 and the face image / facial expression acquisition unit 206.

In step S12, the human body detection unit 204 detects the human body from the image data. Any known algorithm can be used for human body detection. The human body detection unit 204 outputs a region in the image where the human body is likely to exist. The human body detection unit 204 may identify the human body region in the image by tracking the human body once detected.

In step S13, the posture estimation unit 208 estimates the posture of the human body for the human body region detected by the human body detection unit 205. The posture estimation unit 208 detects the positions of a plurality of skeleton points (feature points) from, for example, the human body region. Examples of skeletal points include nose, eyes, ears, shoulders, elbows, wrists, hips, knees, ankles, and toes, but may or may not include some of these. The posture estimation unit 208 outputs information (skeleton point information) indicating the position of the skeleton point.

In step S14, the face image / facial expression acquisition unit 206 extracts the face image from the image data and acquires the facial expression from the face image. Any known algorithm can be used for face detection. The face image / facial expression acquisition unit 206 outputs a region in the image where the face is likely to exist. The face image / facial expression acquisition unit 206 may specify the face region in the image by tracking the face once detected. The face image / facial expression acquisition unit 206 also estimates the facial expression of the face region. The face image / facial expression acquisition unit 206 obtains the degree (score) that applies to each of the plurality of facial expressions, for example, based on the positional relationship of the feature points in the face image. Examples of facial expressions include joy, surprise, anger, and sadness, but may or may not include some of these. The face image / facial expression acquisition unit 206 outputs a score for each facial expression.

In step S15, the fatigue degree estimation unit 212 estimates (calculates) the fatigue degree of the climber 10. The details of fatigue estimation will be described later.

In step S16, the skill level estimation unit 214 estimates (calculates) the skill level of the mountaineering technique of the mountaineer 10. The details of proficiency estimation will be described later.

In step S17, the information providing unit 222 provides the user with support information for supporting the climber 10. In the present embodiment, the recommended mountain climbing route determined by the recommended route determination unit 216 and the estimated arrival time to the destination estimated by the estimated time estimation unit 218 are provided as support information. Details such as the estimated arrival time, the determination of the recommended mountain climbing route, and the timing of providing support information will be described later.

The recommended route determination unit 216, the estimated time estimation unit 218, and the information providing unit 222 correspond to the support means in the present invention.

(Fatigue estimation process S15)
The details of the fatigue degree estimation process S15 will be described. Fatigue estimation is performed based on the skeleton point information obtained by the posture estimation unit 208 and the face image / facial expression acquired by the face image / facial expression acquisition unit 206. FIG. 4 is a diagram schematically illustrating a fatigue degree estimation process. As shown in FIG. 4, the fatigue degree estimation unit 212 has a walking motion, that is, a decrease amount Δa of the degree of increase of the toe based on the time series information of the skeletal point information, a change Δb of the center of gravity of the upper body, and a face orientation c based on the face image. And the pulse rate d are used to calculate the degree of fatigue. Each parameter will be described below.

The degree of rise of the toe is obtained from the change in the position of the toe in the skeletal point information. As described above, since the aviation drone 100 photographs the climber 10 at a certain distance from the upper front, the fatigue degree estimation unit 212 calculates the degree of rise of the toe from the Y coordinate position in the image of the toe position. it can. The degree of raising of the toe is obtained as, for example, the maximum value of the difference between the Y coordinate of the front foot and the Y coordinate of the rear foot in one walking motion. In addition, it is preferable to calculate the degree of toe rise in a place where the road is flat. Therefore, for example, it is preferable to perform the operation when it is determined by the barometric pressure sensor (altitude sensor) or the ultrasonic sensor of the aviation drone 100 that there is no inclination (altitude difference). Alternatively, when there is an inclination, the degree of raising of the toe may be obtained and correction may be made according to the degree of inclination.

The fatigue degree estimation unit 212 stores the rising degree of the toe at the start of mountain climbing, and obtains the current rising condition of the toe and the decrease amount Δa of the rising condition of the toe at the start of mountain climbing. It should be noted that, since the degree of rise of the toes generally decreases with the passage of time, Δa basically takes a positive value.

Here, the change in the degree of rise is obtained for the toes, but since it is sufficient to obtain the change in the degree of rise of the foot, it is also possible to obtain the change in the degree of rise and the degree of rise for the ankle or knee. A similar effect can be obtained.

The center of gravity of the upper body is determined as the position of the center of gravity of the skeletal points (for example, shoulders and hips) of the upper body. In the present embodiment, the fatigue degree estimation unit 212 obtains the difference (decrease amount) between the distance between the center of gravity of the upper body and the center of gravity of the face at the start of mountain climbing and the present as the change Δb of the center of gravity of the upper body. As the distance between the center of gravity of the upper body and the center of gravity of the face becomes shorter, it can be determined that the center of gravity is closer to the front. Since it is common to bend forward with the passage of time, Δb basically takes a positive value.

Although the center of gravity of the face is used as a reference point when determining the change in the center of gravity of the upper body, other positions such as the skeletal points of the waist and ankle may be used.

The face orientation c is obtained from the face image. In the present embodiment, the face orientation c represents how much the face orientation is downward from the front. In the present embodiment, the value of c takes 0 when facing the front, a positive value when facing downward, and a negative value when facing upward. The face orientation c is considered to represent the degree of depression of the face orientation of the climber 10.

The pulse rate d is determined based on the change in color or brightness in the facial image. Fatigue estimation unit 212 can use any known algorithm for obtaining the pulse rate from the facial image. The pulse rate d is obtained as the number of pulses per unit time.

The above parameters may be obtained from one image, but may be an average value in a plurality of images (multiple time points).

The fatigue degree estimation unit 212 calculates the current fatigue degree of the walking climber 10 by using the above information. If during walking, fatigue level estimation unit 212, according to the following equation (1), determine the fatigue s _t at the current (time t).
s _t = f (Δa, Δb, c, d) ... (1)

Here, take a larger value are tired fatigue s _t, s _{t = 0} means that there is no fatigue. The function f takes a larger value as Δa increases (the greater the amount of decrease in the degree of increase of the toe). The function f takes a larger value as Δb becomes larger (the center of gravity of the upper body bends forward). The function f takes a larger value as c is larger (the face is facing downward, in other words, the degree of depression is larger). The function f takes a larger value as d is larger (the faster the pulse is).

On the other hand, if the climber 10 is taking a break, the fatigue degree estimation unit 212 estimates the current fatigue degree from the amount of recovery according to the fatigue degree at the start of the break and the break time. More specifically, the fatigue degree estimation unit 2
12 obtains the current fatigue _{s t} according to the following equation (2).
s _t = s'× g (t−t') ・ ・ ・ (2)

Here, s'is the degree of fatigue at the start of the break, and t'is the time at the start of the break. The function g is g (0) = 1, and is a decreasing function that asymptotically approaches 0 with the passage of time. The function g may be obtained by experiment in advance, for example.

Here, an example of calculating the degree of fatigue based on the change in the degree of rise of the toes, the change in the center of gravity of the upper body, the direction of the face, and the pulse rate is shown, but it is not necessary to use all of these parameters. The degree of fatigue may be calculated using parameters other than these.

Examples of other parameters include steps, stride length, number of posture collapses, facial expressions, and respiratory status.

The number of steps can be obtained from the skeletal point information. Specifically, the number of steps at which the Y coordinate of the right foot and the Y coordinate of the left foot are exchanged can be obtained as the number of steps. The fatigue degree estimation unit 212 stores the number of steps per unit time at the start of mountain climbing, and obtains how much the current number of steps per unit time has decreased from the start of mountain climbing. The fatigue degree estimation unit 212 estimates that the greater the decrease in the number of steps, the higher the degree of fatigue. The number of steps may be calculated only on a flat place.

The stride length is obtained from the number of steps per unit time and the distance traveled by the air drone 100 or the information terminal 200 in the unit time. The fatigue degree estimation unit 212 stores the stride at the start of mountain climbing, and obtains how much the current stride has decreased from the start of mountain climbing. The fatigue degree estimation unit 212 estimates that the greater the decrease in stride length, the higher the degree of fatigue.

It can be determined that the posture collapse occurred when the total amount of changes (absolute values) of the coordinates of all the skeleton points in a short time was equal to or more than the threshold value. For example, the posture collapse can be determined based on the change in the position of the skeleton point between consecutive frames. The fatigue level estimation unit 212 estimates that the greater the number of posture collapses within the most recent predetermined period, the higher the fatigue level.

The facial expression is obtained from the facial image. The fatigue degree estimation unit 212 estimates that the higher the degree of suffering in the facial expression of the climber 10, the higher the degree of fatigue.

The respiratory rate can be obtained from the facial image as well as the pulse rate. The fatigue level estimation unit 212 estimates that the higher the respiratory rate per unit time of the climber 10 or the larger the increase amount, the higher the fatigue level.

(Skill level estimation process S16)
The details of the skill level estimation process S16 will be described. The skill level estimation is performed based on the pre-input information p input in advance, the skeleton point information obtained by the posture estimation unit 208, and the fatigue level estimated by the fatigue level estimation unit 212. FIG. 5 is a diagram schematically illustrating the skill level estimation process. As shown in FIG. 5, the proficiency level estimation unit 214 has a walking motion, that is, a change in stride length Δq based on time-series information of skeletal point information, a change in speed Δr, a frequency n of posture collapse, and fatigue. The skill level is estimated using the change Δs of the fatigue level s estimated by the degree estimation unit 212. Each parameter will be described below.

The pre-entered information is information pre-entered by the climber 10 and includes at least one of years of climbing experience, number of climbs, equipment, and self-reported skill level. The skill level estimation unit 214 stores the pre-input information a in the memory. The input information may be stored as it is, or the skill level derived from the input information may be stored.

The stride length is obtained from the number of steps per unit time and the distance traveled by the air drone 100 or the information terminal 200 in the unit time. The number of steps can be obtained from the skeletal point information. Specifically, the number of steps at which the Y coordinate of the right foot and the Y coordinate of the left foot are exchanged can be obtained as the number of steps. The stride q can be obtained by dividing the distance traveled per unit time by the number of steps. The skill level estimation unit 214 stores the stride at the start of mountain climbing, and obtains the amount of decrease in the current stride from the start of mountain climbing as the change in stride Δq. Since the stride generally decreases with the passage of time, Δq basically takes a positive value.

The speed is obtained from the distance traveled by the air drone 100 or the information terminal 200 in a unit time. The speed can also be obtained from the number of steps per unit time and the average interval per step. The skill level estimation unit 214 stores the speed at the start of mountain climbing, and obtains how much the current speed has decreased from the start of mountain climbing. The skill level estimation unit 214 estimates that the greater the decrease in speed, the higher the degree of fatigue.

It can be determined that the posture collapse occurred when the total amount of changes (absolute values) of the coordinates of all the skeleton points in a short time was equal to or more than the threshold value. For example, the posture collapse can be determined based on the change in the position of the skeleton point between consecutive frames. The proficiency level estimation unit 214 obtains the number n of posture collapses within the latest predetermined period.

The change Δs of the fatigue degree is the degree of increase of the fatigue degree s calculated by the fatigue degree estimation unit 212. The skill level estimation unit 214 may obtain the difference between the fatigue level before a predetermined period and the current fatigue level as Δs, or may obtain a value obtained by weighting the difficulty level of the mountain climbing route as Δs. .. It is appropriate to obtain the change Δs of the degree of fatigue when the climber 10 is walking.

Using the above information, the skill level estimation unit 214 calculates the skill level P of the walking climber 10 according to the following formula (3).
P = p + h (Δq, Δr, n, Δs) ... (3)

Here, the greater the skill level P, the more skilled the mountaineer is. The function h takes a larger value as Δq becomes smaller (the smaller the decrease in stride length). The function h takes a larger value as Δr becomes smaller (the smaller the decrease in velocity). The function h takes a larger value as n is smaller (the number of posture collapses is smaller). The function h takes a larger value as Δs becomes smaller (the smaller the increase in the degree of fatigue).

(Support information provision process S17)
The details of the support information providing process S17 will be described. In this embodiment, the recommended route is provided and the estimated arrival time to the destination is presented. It is not necessary to provide both of these information, and information on only one of them may be provided.

(Route recommended)
First, the provision of the recommended route will be described with reference to FIG. In step S20, the recommended route determination unit 216 calculates the state score based on the state information of the climber 10. Here, the state information of the climber 10 includes the fatigue level s and the skill level P. The state score is calculated as the skill level P is larger and the fatigue level s is smaller.

In step S21, it is determined whether or not the current location is a branch point of the mountain climbing route. Since the mountain climbing database 220 stores the mountain climbing route in advance, the recommended route determination unit 216 has the current location as a branch point based on the current position obtained from the air drone 100 or the information terminal 200 and the mountain climbing database 220. Can be judged. The fact that the current location is a branch point may include the climber 10 reaching the branch point within a predetermined time.

At the branch point (S21-YES) of the mountain climbing route, the process proceeds to step S22. The recommended route determination unit 216 acquires a difficulty score for each mountain climbing route after the branch at the branch point. It is assumed that the mountain climbing database 220 stores the difficulty score in advance for each mountain climbing route. Therefore, the recommended route determination unit 216 can acquire the difficulty score of each mountain climbing route after branching by referring to the mountain climbing database 220.

In step S23, the recommended route determination unit 216 determines whether or not any of the climbing routes after branching has a difficulty score higher than the state score of the climber 10. If there is a mountain climbing route with a difficulty level higher than the state score (S23-YES), the process proceeds to step S24. If not (S23-NO), the process ends without doing anything.

In step S24, the recommended route determination unit 216 determines as a recommended route a mountain climbing route having a difficulty score (less than or equal to the state score) that matches the state score of the climber 10. When there are a plurality of routes that match the state score, only a part of them may be determined as the recommended route, or all of them may be determined as the recommended route. The information providing unit 222 notifies the mountain climber 10 by displaying the mountain climbing route recommended by the recommended route determining unit 216 on the display of the information terminal 200 or providing voice guidance from the speaker.

Here, it is assumed that the climber 10 presents the recommended route before selecting the route, but when the climber 10 is going on a climbing route with a difficulty level higher than the state score (actually). The recommended route may be presented at (including the case where the route is advanced to). Further, even if there is no mountaineering route having a difficulty level higher than the state score of the mountaineer 10, support information for each mountaineering route may be provided.

Next, a case where it is determined that the current location is not a branch point in the determination in step S21 (S21-NO) will be described. In this case, the process proceeds to step S25.

In step S25, the recommended route determination unit 216 acquires the difficulty score of the current mountain climbing route from the mountain climbing database 220.

In step S26, the recommended route determination unit 216 determines whether or not the difficulty score of the current mountaineering route is higher than the state score of the mountaineer 10. If the difficulty score of the mountain climbing route is not higher than the state score of the mountain climber 10 (S26-NO), the process ends without doing anything. If the difficulty score of the mountain climbing route is higher than the state score of the mountain climber 10 (S26-YES), the process proceeds to step S27, and the recommended route determination unit 216 determines that a break should be recommended. The information providing unit 222 recommends that the climber 10 take a break by displaying the information on the display of the information terminal 200 or providing voice guidance from the speaker.

When recommending a break, the information providing unit 222 may notify at least how long the break should be taken in consideration of the recovery of the fatigue level based on the equation (2). For example, the time required for the fatigue level to recover to the extent that the state score of the mountaineer 10 is sufficiently higher than the difficulty score of the mountaineering route may be calculated and notified to the mountaineer 10. If the state score does not match the difficulty score of the mountain climbing route even after taking a break for a predetermined time or longer, the information providing unit 222 may recommend descending the mountain (returning the mountain climbing route).

In the above description, the score obtained from the mountain climbing database 220 is used as the difficulty score of the mountain climbing route, but the difficulty score may be determined in consideration of the current state of the mountain climbing route. For example, the aviation drone 100 may temporarily interrupt the tracking of the climber 10 when the fork is approaching or periodically, and photograph the situation of the climbing route ahead by the camera 102. Then, the difficulty level of the mountain climbing route may be determined based on the captured image. For example, when the road is muddy or a tree has fallen and the road is blocked, the difficulty score stored in the mountain climbing database 220 may be corrected to a higher difficulty level.

(Estimated arrival time)
Next, the provision of the estimated arrival time to the destination will be described with reference to FIG. 7. In step S31, the estimated time estimation unit 218 determines the standard time required between the two most recent checkpoints passed by the climber 10 and the standard between the most recent checkpoint and the destination (the final checkpoint on the mountaineering route). Get the required time. The mountain climbing database 220 stores in advance the standard required time between a plurality of checkpoints set in the mountain climbing route. Therefore, the estimated time estimation unit 218 can obtain the standard required time between checkpoints by referring to the mountain climbing route database 220.

In step S32, the estimated time estimation unit 218 is based on the actual time required between the two most recent checkpoints, the fatigue level of the climber 10, the increase in fatigue level, the skill level, and the standard time required to reach the destination. , Calculate the estimated arrival time to the destination.

A more specific description will be given with reference to FIG. In FIG. 8, the point B represents the latest checkpoint, the point A represents the checkpoint before the point B, and the point C represents the destination. The estimated required time H required to reach the point C (destination) after departing from the point B can be calculated according to the following equation (4).
H = (T _AB / E _AB ) x f (s _B , Δs _AB ) x g (P _B ) x E _BC ... (4)

Here, T _AB is the actual time required between _AB , E _AB and E _BC are the standard time required between AB and BC, respectively, s _B is the degree of fatigue at point B, and Δs _AB is the degree of fatigue between AB. , P _B indicates the skill level at point B.

The function f is a function that takes 1 at the standard fatigue level s _B and the fatigue level increase Δs _AB at the point B. The function f is also an increasing function for each of s _B and Δs _AB . The function g takes 1 at the standard skill level P _B at point B and is a decreasing function for P _B. It should be noted that the functions f and g in the equation (4) are different from the functions in the equations (1) and (2).

Since the formula (4) is a formula for obtaining the estimated time from the checkpoint B to the destination C, if the time has passed since the climber 10 passed the checkpoint B, the destination C It is necessary to obtain the estimated required time up to by subtracting the elapsed time from the time obtained from the equation (4).

Both the route recommendation and the estimated arrival time to the destination may be presented, or only one of them may be presented. When both are performed, for example, when the recommended route is presented, the estimated arrival time to the destination may be presented at the same time.

<Advantageous effect>
According to the present embodiment, since the current state of the climber is obtained in real time, an appropriate route can be recommended at the present time, and a more accurate estimated arrival time can be provided. In this way, it is possible to provide more appropriate support information than before.

<Modification example>
The above embodiment is only one specific example, and the present invention can be implemented by adding various modifications within the scope of its technical idea.

For example, instead of an aerial drone, a ground drone that moves on the ground may be used to track and photograph the climber 10. Further, the number of drones does not have to be one, and the climber 10 may be tracked and photographed by a plurality of drones.

Further, in the above description, the information terminal 200 executes all the processing of the flowchart shown in FIG. 3, but a device other than the information terminal 200 may perform some or all of the processing. For example, the aviation drone 100 may perform some or all of these processes. Further, a device other than the aviation drone 100 and the information terminal 200 may cooperate with the information terminal 200 to realize the process shown in FIG. When a plurality of devices execute the process shown in FIG. 3, the combination of the devices corresponds to the mountaineer support device in the present invention.

<Additional notes>
(1) An image acquisition means (202) that acquires the image from the tracking device (100) that tracks the mountaineer and captures the image of the mountaineer.
Analytical means (212, 214) for analyzing the image to acquire state information of the climber including at least one of the climber's fatigue level (s) and skill level (P).
Support means (216, 218, 220) for providing support information for supporting mountain climbing to the mountaineer based on the state information of the mountaineer, and
Climber support device (200).

(2) A climber support method executed by the computer (200).
An image acquisition step (S11) of acquiring the image from the tracking device (100) that tracks the mountaineer and captures the image of the mountaineer.
An analysis step (S15, S16) of analyzing the image to acquire state information of the mountaineer including at least one of the degree of fatigue and skill of the mountaineer.
A support step (S17) for providing support information for supporting mountain climbing to the mountaineer based on the state information of the mountaineer, and
Climber support methods, including.

10: Climber 100: Air drone 200: Information terminal

Claims (19)

An image acquisition means for acquiring the image from a tracking device that tracks the climber and captures the image of the climber.
An analysis means for analyzing the image to acquire state information of the mountaineer including at least one of the degree of fatigue and skill of the mountaineer.
A support means for providing support information for supporting mountain climbing to the mountaineer based on the state information of the mountaineer, and
Climber support device equipped with. The analysis means
Posture estimation means for estimating the skeleton point of the climber and
Fatigue estimation means for estimating fatigue based on the movement of skeletal points, and
To prepare
The mountaineer support device according to claim 1. The fatigue degree estimating means estimates the fatigue degree according to a change in the degree of foot rise.
The mountaineer support device according to claim 2. The fatigue degree estimating means estimates the fatigue degree according to a change in the center of gravity of the upper body.
The mountaineer support device according to claim 2 or 3. The fatigue degree estimating means estimates the fatigue degree according to a change in the number of steps or a stride length.
The mountaineer support device according to any one of claims 2 to 4. The analysis means estimates the degree of fatigue from the image based on the face image of the climber.
The mountaineer support device according to any one of claims 2 to 5. The fatigue degree estimating means estimates the fatigue degree according to the degree of depression of the mountaineer's face orientation.
The mountaineer support device according to claim 6. The fatigue degree estimating means estimates the fatigue degree according to the pulse rate obtained from the face image.
The mountaineer support device according to claim 6 or 7. The analysis means further includes a determination means for determining whether or not the climber is taking a break from the image.
When the climber is taking a break, the fatigue degree estimating means estimates the current fatigue degree from the fatigue degree at the start of the break and the amount of recovery according to the break time.
The mountaineer support device according to any one of claims 2 to 8. The analysis means
Posture estimation means for estimating the skeleton point of the climber and
A skill level estimation means for estimating the skill level of the climber based on at least one of the number of steps or the change in stride length obtained from the skeleton point and the frequency of losing posture.
To prepare
The mountaineer support device according to any one of claims 1 to 9. Further equipped with a memory means to memorize the mountain climbing route in relation to the difficulty level,
The support means calculates a score from the degree of fatigue or skill of the climber, determines a climbing route of a difficulty level corresponding to the score, and provides the determined climbing route as the support information.
The mountaineer support device according to any one of claims 1 to 10. The support means provides the support information when the climber intends to proceed to a mountaineering route having a difficulty level higher than the difficulty level corresponding to the score according to the fatigue level or the skill level.
The mountaineer support device according to claim 11. The support means provides the estimated time of arrival at the destination as the support information.
The mountaineer support device according to any one of claims 1 to 12. The support means includes the standard required time and the actual required time from the first checkpoint to the second checkpoint, the degree of fatigue at the second checkpoint, and the second checkpoint from the first checkpoint. The estimated arrival time at the destination is calculated based on the increase in the degree of fatigue up to the checkpoint and the standard required time from the second checkpoint to the destination.
The mountaineer support device according to claim 13. The mountaineer support device according to any one of claims 1 to 14,
A tracking device that tracks the climber and captures an image of the climber,
Climber support system equipped with. The tracking device is an air vehicle including imaging means.
The mountaineer support system according to claim 15. The tracking device tracks the mountaineer so that he / she can face the mountaineer and photograph the mountaineer at a predetermined distance and a predetermined angle.
The mountaineer support system according to claim 16. It ’s a computer-run method of supporting climbers.
An image acquisition step of acquiring the image from a tracking device that tracks the climber and captures the image of the climber.
An analysis step of analyzing the image to acquire state information of the climber including at least one of the climber's fatigue level and skill level, and
A support step that provides support information for supporting mountain climbing to the mountaineer based on the state information of the mountaineer, and a support step.
Climber support methods, including. A program that causes a computer to function as each means of the mountaineer support device according to any one of claims 1 to 14.

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