Input device, input system, input method, and recording medium

Abstract

In the input device (100), the position detection section (110) detects the position of the operation body (300) sliding on the operation surface (200). The pressing force detection section (120) detects the pressing force of the operation body (300) pressing the operation surface (200) at the position detected by the position detection section (110). The recording section (130) acquires the position of the operation body (300) from the position detection section (110), acquires the pressing force of the operation body (300) at the position from the pressing force detection section (120), and records the history thereof. The feature extraction section (140) extracts data indicating the feature of the sliding of the operation body (300) from the history of the position and the pressing force of the operation body (300) recorded by the recording section (130).

Description

Technical Field

[0001] This invention relates to input devices, input systems, input methods, and recording media. Background Technology

[0002] Smartphones and tablets are well-known examples of devices that integrate the touch panel for both operation and display. In such devices, users can input data and give instructions by lightly touching the touch panel with their fingers and making swipe gestures.

[0003] Furthermore, in recent years, devices have been proposed that read the pressure intensity of a user's finger pressing a touch panel and convert it into an indication. For example, Patent Document 1 discloses a tablet terminal that records the history of the contact pressure of a user pressing a touch panel and creates messages corresponding to the magnitude and duration of the contact pressure.

[0004] Patent Document 1: Japanese Patent Application Publication No. 2015-176490 Summary of the Invention

[0005] The information processing device described in Patent Document 1 obtains the characteristic quantity of the contact pressure and converts it into data, but it cannot cope with the sliding operation of the contact point movement.

[0006] When operating a touch panel, most operations involve swiping. Swiping involves not only changes in the position of the contact point but also changes in the pressure applied. However, existing input methods do not utilize this information.

[0007] The present invention was proposed in view of the above-mentioned actual situation, and its purpose is to properly detect sliding operations on a touch panel.

[0008] To achieve the above objectives, the input device of the present invention includes: a position detection unit that detects the position of an operating body sliding on an operating surface; a pressure detection unit that detects the pressure of the operating body pressing against the operating surface at the position detected by the position detection unit; a recording unit that obtains the position of the operating body from the position detection unit, obtains the pressure generated by the operating body at that position from the pressure detection unit, and records their history; and a feature extraction unit that extracts the sliding feature quantity generated by the operating body from the history of the position and pressure of the operating body recorded by the recording unit.

[0009] The effects of the invention

[0010] According to the present invention, the pressure detection unit detects the pressure applied by the operating body to the operating surface, and the recording unit records the history of characteristic quantities, including the detected pressure. Therefore, sliding operations on the touch panel can be appropriately detected. Attached Figure Description

[0011] Figure 1 This is a diagram illustrating the functional structure of the input device involved in the implementation method.

[0012] Figure 2A This diagram illustrates an example of a situation where the character detected by the input device according to Embodiment 1 is displayed solely by its position.

[0013] Figure 2B This is a diagram illustrating an example of how the character detected by the input device according to Embodiment 1 is displayed by position and pressure.

[0014] Figure 2C This is a diagram illustrating an example of how the character detected by the input device according to Embodiment 1 is displayed by position and pressure.

[0015] Figure 3 This is a diagram illustrating the feature points of an example of a character detected by the input device according to Embodiment 1.

[0016] Figure 4A This is a flowchart illustrating the handwriting registration process involved in Implementation Method 1.

[0017] Figure 4B This is a flowchart illustrating the handwriting comparison process involved in Implementation Method 1.

[0018] Figure 5 This is a flowchart illustrating the record processing involved in Implementation Method 1.

[0019] Figure 6 This is a flowchart illustrating the feature extraction process involved in Implementation Method 1.

[0020] Figure 7 This is a diagram used to illustrate the registration data in Implementation Method 1.

[0021] Figure 8 This is a flowchart illustrating the execution process involved in Implementation Method 1.

[0022] Figure 9A This is a diagram illustrating the scenario where a user's finger slides on the touch panel in Embodiment 2.

[0023] Figure 9B This is a diagram illustrating the pressure distribution on the contact surface where the user's finger contacts the touch panel in Embodiment 2.

[0024] Figure 10 This is a diagram illustrating the calculation process of the pressure gradient for approximating the pressure distribution in the contact surface in Embodiment 2.

[0025] Figure 11This is a diagram illustrating the process of calculating the pressure gradient when the pressure distribution has an angle in the implementation method.

[0026] Figure 12 This is a diagram illustrating the scenario where the key device according to Embodiment 3 operates the touch panel.

[0027] Figure 13 This is a diagram illustrating the process of calculating the characteristics of the rotational motion of the key device according to Embodiment 3 on the touch panel.

[0028] Figure 14 This is a diagram showing the structure of the input system involved in Implementation Method 4.

[0029] Figure 15 This is a diagram illustrating the online stamping process in Implementation Method 4.

[0030] Figure 16 This is a diagram showing the structure of the input system involved in Implementation Method 4.

[0031] Figure 17 This is a diagram used to illustrate an example of multiple inputs in Variation Example 1.

[0032] Figure 18 This is a diagram illustrating the hardware structure of the input device and server involved in the implementation method. Detailed Implementation

[0033] Hereinafter, the input device 100 according to embodiments of the present invention will be described in detail with reference to the accompanying drawings. Furthermore, these embodiments are for illustrative purposes and are not intended to limit the scope of the present invention. Therefore, those skilled in the art can employ embodiments in which each or all of the above-described elements are replaced with equivalent elements, but these embodiments are also included within the scope of the present invention.

[0034] (Implementation Method 1)

[0035] The input device 100 involved in Embodiment 1 is an input device used in smartphones, tablet terminals, etc. For example... Figure 1 As shown, the input device 100 has a touch panel 200 that accepts sliding operations performed by a user's finger or other operating body 300. The input device 100 not only detects the position of the operating body 300 on the touch panel 200, but also detects the pressure applied by the operating body 300 when pressing the touch panel 200 at the detected position, and extracts the sliding features.

[0036] With input device 100 pairs Figure 2AThe following explanation will use the handwriting pattern T0 as an example for detection. Here, the handwriting pattern includes not only handwriting drawn with a writing tool, but also handwriting drawn with a finger. The handwriting pattern T0 depicts the hiragana character "て", starting from the left end and proceeding in the direction of the arrow. Figure 2B , Figure 2C The handwriting patterns T1 and T2, which are formed by applying pressure to the touch panel 200 on the handwriting pattern T0, are depicted respectively. The thickness of the handwriting patterns T1 and T2 indicates the amount of pressure applied at each point that constitutes the handwriting patterns T1 and T2.

[0037] If displayed solely by position, handwriting patterns T1 and T2 are identical to handwriting pattern T0. However, if pressure is applied at each point, handwriting patterns T1 and T2 differ from handwriting pattern T0. Handwriting pattern T1 is characterized by low pressure at the beginning of writing, slightly increased pressure at the right-hand fold, and decreasing pressure towards the end of writing. Handwriting pattern T2 is characterized by high pressure at the beginning of writing, slightly decreasing pressure, slightly increasing pressure at the right-hand fold, slightly decreasing pressure again, and increasing pressure towards the end of writing.

[0038] In this way, the input device 100 can detect the user's handwriting preferences with higher accuracy by evaluating the handwriting based on the pressure applied at each point that constitutes the handwriting. The input device 100 will now be described, which uses the user's handwriting as a signature, compares the input handwriting with pre-registered handwriting, and performs corresponding processing based on the comparison results.

[0039] Return to Figure 1 The functional structure of the input device 100 will be described below. The input device 100 includes: a position detection unit 110 for detecting the position of the operating body 300; a pressure detection unit 120 for detecting the pressure applied to the operating surface; a recording unit 130 for recording the detected position and pressure; and a feature extraction unit 140 for extracting the feature values ​​of the handwriting. The input device 100 also includes: a comparison unit 150 for comparing handwriting; a registration unit 160 for pre-registering the feature values ​​of the handwriting; and an execution unit 170 for performing the processing.

[0040] The position detection unit 110 detects the position of the user's finger or other operating body 300 that slides on the operating surface, i.e., the touch panel 200. In addition, the operating body 300 is not limited to the user's finger, but may also be other devices that can slide on the touch panel 200, such as a stylus or other pointing device, a seal, or a postmark.

[0041] The pressure detection unit 120 detects the pressure applied by the operating body 300 to the touch panel 200 at the position detected by the position detection unit 110 on the operating body 300. That is, the pressure detection unit 120 detects the pressure applied by the operating body 300 to the touch panel 200 simultaneously with the position detection unit 110 detecting the position on the touch panel 200. Furthermore, the position detection unit 110 and the pressure detection unit 120 may also be integrated into one unit.

[0042] The recording unit 130 obtains the position of the operating body 300 from the position detection unit 110, obtains the pressure generated by the operating body 300 at that position from the pressure detection unit 120, and records the position along with the time of acquisition. That is, the recording unit 130 records the position, pressure, and time of each point constituting the handwriting, obtained in fixed time units. Furthermore, the recording unit 130 records the sliding features generated by the operating body 300 extracted by the feature extraction unit 140 (described later). At this time, as the sliding features generated by the operating body 300 extracted by the feature extraction unit 140, the recording unit 130 records the characteristic points on the handwriting, i.e., feature points F, along the sliding trajectory. j The set of (j is a natural number) is used for recording.

[0043] The feature extraction unit 140 extracts data representing the sliding characteristics generated by the operating body 300 from the history of the position and pressure of the operating body 300 recorded by the recording unit 130. For example, the feature extraction unit 140 extracts data representing the sliding characteristics generated by the operating body 300. Figure 3 The illustrated feature points F1 to F7 are used to extract the sliding features generated by the operating body 300. As feature points F... j Based on the position of each point (x) j y j ) and pressure p j The data is recorded in the recording unit 130. Based on position (x j y j ) and pressure p j The data is the location (x) j y j ), pressure p j These include the feature points themselves, their rates of change over time, and their position vectors. Additionally, the feature points F can also be considered. j Simultaneously record the time t at that point. j .

[0044] Feature point F j These are characteristic points in a handwriting pattern (e.g., handwriting pattern T2), such as the start point, end point, inflection point, position, or point where pressure reaches an extreme value. Figure 3In the example shown, feature point F1 is the starting point of handwriting pattern T2. ​​Feature point F1 is the point where the pressure becomes minimum and then begins to increase, i.e., the point where the pressure reaches its minimum value. Feature point F3 is the point where the position and direction of handwriting pattern T2 change drastically, i.e., the point where the position coordinates reach an extreme value. Feature point F4 is the point where the position and direction of handwriting pattern T2 change drastically, and the pressure begins to increase, i.e., the point where the position coordinates reach an extreme value and the pressure reaches its minimum value. Feature point F5 is, for example, the point where the rate of change of pressure is constant, and the concave and convex curves of the pressure-time curve reverse before and after it, i.e., the point where the pressure is at an inflection point. Feature point F6 is the point where the pressure becomes maximum and then begins to decrease, i.e., the point where the pressure reaches its maximum value. Feature point F7 is the ending point of handwriting pattern T2.

[0045] The comparison unit 150 compares the data representing the sliding features generated by the operating body 300 extracted by the feature extraction unit 140 with the data representing the features of the operating body 300 pre-registered by the registration unit 160. The comparison unit 150 determines whether the sliding features generated by the operating body 300 extracted by the feature extraction unit 140 are consistent with the sliding features generated by the operating body 300 registered by the registration unit 160. Here, "consistent" does not only mean completely consistent, but may also include a certain degree of consistency, or something similar. Similarity or dissimilarity is determined by a certain similarity calculation based on whether a benchmark is met.

[0046] The registration unit 160 pre-registers data representing the sliding characteristics generated by the operating body 300. Alternatively, the registration unit 160 may also register the sliding characteristics generated by the operating body 300 recorded by the recording unit 130.

[0047] If the comparison result obtained by the comparison unit 150 is consistent with the data representing the sliding feature generated by the operating body 300 extracted by the feature extraction unit 140 and the data representing the sliding feature generated by the operating body 300 pre-registered by the registration unit 160, the execution unit 170 executes a pre-defined action. The pre-defined action may be, for example, an action to successfully pass the user's authentication, or an action to generate a certain execution command.

[0048] Figure 4A This is a flowchart illustrating the handwriting registration process performed by the input device 100. Figure 4B This is a flowchart illustrating the handwriting comparison process performed by the input device 100. The handwriting registration process is used to register handwriting samples that should be compared using the handwriting comparison process; it is a preparatory process for performing the handwriting comparison. The handwriting comparison process compares the newly received handwriting with the handwriting samples registered in the handwriting registration process and performs processing corresponding to the comparison result. Below, refer to... Figure 4A , 4B and Figures 5-7This section explains the handwriting registration and comparison process.

[0049] In the input device 100, for example, by launching an application for handwriting registration, or by opening a webpage for handwriting registration, the process begins. Figure 4A The handwriting registration process is shown.

[0050] If handwriting registration processing begins, firstly, recording processing for recording the handwriting begins (step S100). Then, triggered by a notification executed during the recording processing (described later), feature extraction processing for extracting handwriting features begins (step S200). Feature extraction processing can be performed in parallel with recording processing.

[0051] Figure 5 This is a flowchart of the recording process. In the recording process, the sliding characteristics generated by the operating body 300 are recorded in the recording unit 130.

[0052] If recording processing begins, the process first enters a waiting state (No in step S101) until the position detection unit 110 and the pressure detection unit 120 each detect the initial input, that is, until the i=0th position and pressure are detected. Here, the i-th position and pressure are obtained in sequence at fixed time intervals. This time interval can also be a time interval based on clock time, which is based on a clock signal generated by clock 60 described later. In this case, the time interval can be the clock time itself or a time several times the clock time.

[0053] If the position and pressure of position i=0 are detected by position detection unit 110 and pressure detection unit 120 (Yes in step S101), recording unit 130 records position i=0 and pressure (step S102). Then, recording unit 130 notifies feature extraction unit 140 of the designation of position i=0 and pressure (step S103).

[0054] Then, the sequence i is incremented (step S104). If the position detection unit 110 and the pressure detection unit 120 detect the i-th position and pressure, which is the first position and pressure in this case (Yes in step S105), the recording unit 130 records the i-th position and pressure (step S106). Then, the recording unit 130 notifies the feature extraction unit 140 of the recorded i-th position and pressure (step S107). After that, the process jumps to step S104.

[0055] On the other hand, in step S105, if the position detection unit 110 and the pressure detection unit 120 each fail to detect the i-th position and pressure (No in step S105), and an idle time has elapsed (Yes in step S108), then the recording process ends. Here, the idle time refers to the time from when no sliding operation generated by the operating body 300 on the touch panel 200 is detected until the sliding operation is considered to have ended. The idle time is preset. Furthermore, in step S108, it is also possible to determine whether a pre-defined specific operation has been detected, instead of observing the idle time. In this case, if the input device 100 detects a specific operation (Yes in step S108), the recording process will be interrupted or ended until the specific operation is detected, and the process enters a waiting state (No in step S108, No in step S105).

[0056] In step S105, after the position detection unit 110 and the pressure detection unit 120 each stop detecting the i-th position and pressure (No in step S105), the process enters a waiting state until a preset idle time has elapsed (No in step S108).

[0057] Next, refer to Figure 6 The feature extraction process that begins in step S103, in which the recording unit 130 specifies the 0th position and pressure and notifies the feature extraction unit 140, will be described.

[0058] If feature extraction processing is started, firstly, the feature extraction unit 140 sets the number i of the point constituting the handwriting to 0, sets the number j of the feature point to 1, and saves the i=0th position and pressure specified by the notification from the recording unit 130 (step S201).

[0059] Next, increment i by 1 (step S202).

[0060] Next, the feature extraction unit 140 determines whether it has received a notification specifying the i-th, i.e., the i=1-th location and pressure (step S203). If the feature extraction unit 140 receives the i-th notification sent in step S107 (Yes in step S203), it saves the location and pressure of the i-th point specified by the notification (step S204).

[0061] Next, the feature extraction unit 140 determines whether the i-th point is equivalent to a feature point (step S205).

[0062] The feature extraction unit 140 identifies points whose feature quantities, obtained by calculating the position and pressure of the operating body 300 using a predefined function, satisfy predefined conditions as feature points. That is, the feature extraction unit 140 defines the position and pressure (x) of the i-th point as feature points. i y i p i ) and the position and pressure of the (i-1)th point (x) i-1 y i-1 p i-1 The difference is the first rate of change, V. i (V) xi V yi V pi ) = (x i -x i-1 y i -y i-1 p i -p i-1 The feature extraction unit 140 then performs calculations on the i-th first rate of change V. i With the (i-1)th first rate of change V i-1 The difference is the second rate of change A. i (A) xi A yi A pi ) = (V xi -V xi-1 V yi -V yi-1 V pi -V pi-1 ) to perform calculations.

[0063] For example, the second rate of change A i The point where the absolute value of any variable is large, or the second rate of change A. i Points with large vector magnitudes are those where the sliding motion generated by the manipulator 300 changes drastically, and these become feature points. Therefore, the feature extraction unit 140, in conjunction with the second rate of change A... i If these relevant values ​​are greater than the predefined values, the point is designated as a feature point.

[0064] Additionally, for example, the second rate of change A i For any variable that is 0, the points where its sign changes before or after it are the inflection points of the variable-time curve, and are thus called feature points. Therefore, the feature extraction unit 140 identifies such points as feature points.

[0065] Alternatively, the feature extraction unit 140 can express the position and pressure detected by the position detection unit 110 and the pressure detection unit 120 as functions of time, and determine whether a point corresponds to a feature point by evaluating the value obtained by performing a second derivative on this function. That is, the feature extraction unit 140 can also determine points whose values ​​obtained by performing a second derivative on the history of position and pressure recorded by the recording unit 130 with respect to time are greater than or equal to a predetermined value as feature points.

[0066] If the feature extraction unit 140 determines that the i-th point is not equivalent to a feature point (No in step S205), the process returns to step S202.

[0067] On the other hand, if the feature extraction unit 140 determines that the i-th point is equivalent to a feature point (Yes in step S205), then the recording unit 130 determines the i-th point as the j-th feature point. As the j-th feature point F... j The recording unit 130 generates position data, pressure data, or their position vectors and characteristic quantities and records them (step S206). As described above, the characteristic quantity is the first rate of change V. i The second rate of change A i Additionally, increment j by 1.

[0068] Next, the handling of this matter is... Figure 4A The handwriting registration process shown includes feature extraction processing, or... Figure 4B The handwriting comparison process shown includes feature extraction for discrimination. Because the current process is... Figure 4A The feature extraction process included in the handwriting registration process shown (referred to as "handwriting registration process" in step S206) will then proceed to step S202.

[0069] Then, i is incremented (step S202), and the feature extraction unit 140 determines whether a notification specifying the i-th position and pressure has been received (step S203). Even if the feature extraction unit 140 does not receive the i-th notification (No in step S203), the processing remains in a waiting state until the idle time has elapsed (No in step S207).

[0070] On the other hand, if the feature extraction unit 140 does not receive the i-th notification (No in step S203) and an idle time has elapsed (Yes in step S207), it determines whether the current processing is part of the handwriting registration process or the handwriting comparison process. Since the current processing is part of the handwriting registration process, the registration unit 160 processes the multiple feature points F recorded up to this point. jThe sliding characteristics generated by the operating body 300 are registered (step S208). That is, the registration unit 160 registers the position data, pressure data, and feature quantity of each feature point of the handwriting. After that, the processing ends. In addition, in step S207, it is also possible to determine whether a pre-defined specific operation has been detected, instead of observing the idle time. In this case, if the input device 100 detects a specific operation (Yes in step S207), the registration unit 160 registers the sliding characteristics generated by the operating body 300 (step S208) until the specific operation is detected (No in step S207, No in step S203), and enters a waiting state.

[0071] If the feature extraction process is complete, the recording unit 130, for example, through... Figure 7 The table shown records the feature values ​​of the handwriting detected by the input device 100. For example, this table records the user's identification information, the handwriting feature points F1, F2, F3, ..., F... n , representing feature point F j The data represents the feature quantity. Here, as an example, F is used to represent the feature point. j The feature data records x j y j p j V j A j .

[0072] Next, refer to Figure 4B The handwriting comparison process is explained. In this process, the sliding of the user-implemented operation body 300 is detected and compared with the registered handwriting. The corresponding processing is then performed based on the comparison result.

[0073] Starting with the handwriting comparison process, the recording process (step S100) begins, which involves recording the handwriting; the feature extraction process (step S200) begins, which involves extracting the features of the handwriting. Furthermore, the recording process and feature extraction process described here are consistent with those described so far. Figure 5 The recording processing and Figure 6 The feature extraction process shown is essentially the same. Then, based on the notification performed in the feature extraction process (described later), the execution process (step S300) begins, performing the pre-defined processing. The feature extraction process can be executed in parallel with the recording process. In addition, the execution process can be executed in parallel with the feature extraction process.

[0074] After starting the handwriting comparison process, until Figure 6 Up to step S206 of the feature extraction process shown, and Figure 4A The record processing shown is the same.

[0075] exist Figure 6 In step S206 of the feature extraction process shown, if the recording unit 130 records the feature points F extracted by the feature extraction unit 140... j Since the current processing is part of the feature extraction process included in handwriting comparison processing, the recorded feature points F... j The reference unit 150 is notified to specify the reference (step S209). At this time, the recording unit 130 can also simultaneously record the reference based on the feature point F. j The location and pressure data are recorded together and specified.

[0076] Furthermore, in step S203, if the feature extraction unit 140 does not receive the i-th notification (No in step S203) and an idle time has elapsed (Yes in step S207), then the processing ends because the current processing is the feature extraction processing included in the handwriting comparison processing. Alternatively, in step S207, a determination can be made regarding whether a pre-defined specific operation has been detected, instead of observing the idle time. In this case, if the input device 100 detects a specific operation (Yes in step S207), the input device 100 ends the processing until the specific operation is detected (No in both step S207 and S203), entering a waiting state.

[0077] Next, refer to Figure 8 In step 209, the recording unit 130 specifies feature point F. j The execution process, which begins upon notification to the control unit 150, is explained.

[0078] If the processing begins, firstly, the comparison unit 150 compares the feature points F. j The determination is made as to whether the amount of data is sufficient to represent the sliding characteristics generated by the operating body 300 (step S301). The comparison unit 150, for example, determines this by analyzing feature points F. j The system determines whether the amount of data is sufficient by checking whether the accumulated data is greater than or equal to a pre-defined value.

[0079] If feature point F j If the amount of data is sufficient (Yes in step S301), then the comparison unit 150 will use multiple feature points F j The feature values ​​of the represented handwriting are compared with the feature values ​​of the handwriting registered in the registration unit 160 to determine whether they are consistent (step S302). That is, the comparison unit 150 uses similarity calculations, etc., to determine whether the feature values ​​extracted from the handwriting formed by the user's current swipe action are consistent with the feature values ​​pre-registered in the registration unit 160. For example, if the comparison unit 150 determines that multiple feature points F of the current handwriting are consistent...j If the similarity between the feature quantity and the feature quantity of the handwriting registered in the registration department 160 is greater than or equal to the reference value, then the handwriting input this time is judged to be consistent with the registered handwriting.

[0080] If the comparison unit 150 determines that the comparison result is consistent (Yes in step S302), the execution unit 170 executes a pre-defined process (step S303). This pre-defined process may include, for example, unlocking the smartphone screen or logging into a webpage. Alternatively, it could be a process for performing a specific action by generating and executing a certain execution command. Afterward, the execution process ends, and the handwriting comparison process also ends.

[0081] On the other hand, if the comparison unit 150 determines that there is an inconsistency in step S302, the execution unit 170 does not perform the pre-defined processing (step S304). After that, the execution processing ends, and the handwriting comparison processing also ends.

[0082] Additionally, in step S301, at feature point F j If the amount of data is insufficient (No in step S301), the comparison unit 150 waits for feature point F. j Further notification (step S305). Without notification of new feature point F j In the case of (No in step S305), the process enters a waiting state until the idle time has elapsed (No in step S306). Here, if a new feature point F is notified... j (If the answer is Yes in step S305), the process jumps to step S301.

[0083] On the other hand, if the new feature point F is not notified j (If the condition is No in step S305), and an idle time has elapsed (if the condition is Yes in step S306), the process jumps to step S304 without executing the pre-defined process. Afterwards, the execution of the process and the handwriting comparison process conclude.

[0084] As described above, according to Embodiment 1, when the input device 100 detects a slide generated by the operating body 300, it not only detects the position coordinates but also the pressure applied to the touch panel 200. Based on the history of position coordinates and pressure, it evaluates the handwriting. Therefore, it is possible to detect handwriting features that cannot be fully represented by position coordinates alone, thereby enabling more precise detection of the user's preferences.

[0085] Furthermore, according to Embodiment 1, during the period when a sliding operation generated by the operating body 300 is received, the process of extracting the feature is started, and a comparison operation with the registered sliding operation begins. Therefore, even during the sliding operation, calculations can be continuously and dynamically performed, enabling smoother processing.

[0086] (Implementation Method 2)

[0087] Next, Embodiment 2 of the present invention will be described. Structures and processes equivalent to those in Embodiment 1 will be labeled with the same reference numerals. In Embodiment 1, the sliding generated by the operating body 300 was detected at a point, but in Embodiment 2, the detection is performed on a surface.

[0088] Figure 9A This shows the user's finger, i.e., the operating body 300, sliding on the touch panel 200 in the direction of the arrow. Figure 9B The pressure distribution detected by the input device 100 according to Embodiment 2 is shown. For example... Figure 9B As shown in the example, the input device 100 determines the contact surface CS where the operating body 300 contacts the touch panel 200, and detects and evaluates its pressure distribution PD. Figure 9B In the example shown, the pressure distribution PD at the contact surface is represented by 3 levels, with higher concentrations indicating greater pressure.

[0089] The position detection unit 110 extracts the contact surface CS between the operating body 300 and the operating surface, i.e., the touch panel 200. The position detection unit 110 periodically detects the contact surface CS formed between the touch panel 200 and the operating body 300.

[0090] The pressure detection unit 120 detects the pressure distribution PD in the contact surface CS detected by the position detection unit 110.

[0091] The recording unit 130 records the history of the contact surface CS and the pressure distribution PD in the contact surface CS detected by the position detection unit 110 and the pressure detection unit 120. In addition, the recording unit 130 can also record the history of the approximate pressure gradient in the contact surface CS calculated by the calculation unit 131, which will be described next.

[0092] like Figure 1 As shown, the input device 100 may also include a calculation unit 131. The calculation unit 131 calculates an approximate pressure gradient for the pressure distribution PD in the contact surface CS extracted by the position detection unit 110 and the pressure detection unit 120. In this case, the calculation unit 131... Figure 5 After step S105, based on the i-th contact surface CS (CS detected by the position detection unit 110 and the pressure detection unit 120) i Pressure distribution in PD (PD)i The approximate pressure gradient is calculated.

[0093] Figure 10 The diagram above shows an example of the pressure distribution PD in the contact surface CS extracted by the position detection unit 110 and the pressure detection unit 120 at a certain instant, and the diagram below shows an example of a curve illustrating the increase or decrease of the pressure distribution PD. Figure 10 The example shown illustrates the highest point of the pressure distribution PD, i.e., the highest pressure point P. O The applied pressure is biased to the right of the geometric centroid G of the contact surface CS.

[0094] When calculating the pressure gradient approximating the pressure distribution PD, the calculation unit 131 first divides the pressure distribution PD into several equal parts according to the magnitude of the pressure (in... Figure 10 In the example, it is divided into 3 equal parts). That is, the calculation unit 131, for example, is as follows: Figure 10 The curve is shown in the figure, with respect to the highest pressure point P. O Pressure P at the point O and the lowest pressure point P C Pressure p at the point c The pressure p = p when divided into 3 equal parts A and p=p B The pressure distribution PD is segmented. Here, the pressure gradient P is... D With p=p O p=p A p=p B p=p C The points of intersection, starting from the left side of the curve, are designated as A, B, C, O, C', B', and A'.

[0095] Next, the calculation unit 131 calculates the slopes of lines AB, BC, CO, OC', C'B', and B'A'. Then, the calculation unit 131 combines the calculated slopes of lines AB, BC, CO, OC', C'B', and B'A', the position of the geometric centroid G, and the point representing the highest pressure P. O The location, etc., are determined as the pressure gradient for approximating the pressure distribution PD.

[0096] like Figure 11 As shown in the example, at the highest pressure point P O In the case of a slope θ, the calculation unit 131 further determines the pressure gradient by taking the slope θ into account. In this case, the calculation unit 131 considers the geometric centroid G passing through the contact surface CS and the highest pressure point P. OThe evaluation surface, y = tanθ·x + const, is used to calculate the slopes of the lines AB, BC, CO, OC', C'B', and B'A' that cut through the pressure distribution PD with the evaluation surface. Then, the calculation unit 131 combines the calculated evaluation surface, the slopes of the lines AB, BC, CO, OC', C'B', and B'A' that cut through the pressure distribution PD with the evaluation surface, the position of the geometric centroid G, and the point representing the highest pressure P. O The location, etc., are determined as the pressure gradient for approximating the pressure distribution PD.

[0097] The feature extraction unit 140 extracts data representing the sliding characteristics generated by the operating body 300 from the history of the pressure distribution PD recorded by the recording unit 130. Alternatively, the feature extraction unit 140 can also extract data representing the sliding characteristics generated by the operating body 300 from the history of the pressure gradient recorded by the recording unit 130. The feature extraction unit 140 can also extract feature points Fi from the history of the pressure distribution PD or its pressure gradient to describe the sliding characteristics generated by the operating body 300. In other words, the feature extraction unit 140 extracts data representing the history of the pressure distribution PD or its pressure gradient in the contact surface CS recorded by the recording unit 130.

[0098] The comparison unit 150 compares the data recorded by the recording unit 130, which represents the history of the pressure distribution PD in the contact surface CS, with the data recorded by the registration unit 160, which represents the history of the contact surface CS. R Pressure distribution in PD R The comparison unit 150 compares the data representing the characteristics of the sliding caused by the operating body 300 extracted by the feature extraction unit 140 with the data representing the characteristics of the sliding caused by the operating body 300 registered by the registration unit 160. Alternatively, the comparison unit 150 can also compare the data representing the characteristics of the pressure gradient history recorded by the recording unit 130 with the data representing the characteristics of the pressure gradient history registered by the registration unit 160. Therefore, the comparison unit 150 compares the data representing the characteristics of the sliding caused by the operating body 300 extracted by the feature extraction unit 140 with the data representing the characteristics of the sliding caused by the operating body 300 pre-registered by the registration unit 160.

[0099] Registration section 160 indicates the contact surface CS generated by operating body 300. R Pressure distribution in PD R The data representing the characteristics of the resume is registered. The registration unit 160 can also register data representing the contact surface CS generated by the operating body 300. R Pressure distribution in PD R The data provides a characteristic of the approximate pressure gradient history.

[0100] Furthermore, in this embodiment, the user's finger is used as an example of the operating body 300, but the operating body 300 is not limited to the user's finger. For example, the operating body 300 may be a stylus with a non-pointed tip and a contact surface CS that contacts the touch panel 200, or a writing instrument such as a marker, or a stationery such as an eraser, seal, or postmark.

[0101] As described above, according to Embodiment 2, when the input device 100 detects a slide generated by the operating body 300, it extracts the pressure distribution PD in the contact surface CS where the operating body 300 contacts the touch panel 200, and evaluates the slide generated by the operating body 300 based on the history of the pressure distribution PD. This allows for a more detailed recording of the slide generated by the operating body 300, and thus enables more accurate detection of the user's preferences.

[0102] (Implementation Method 3)

[0103] Next, Embodiment 3 of the present invention will be described. Structures and processes equivalent to those in Embodiments 1 and 2 will be labeled with the same reference numerals. In Embodiment 3, the cross-sectional shape of the operating body when in contact with the touch panel 200 is identified.

[0104] In implementation method 3, such as Figure 12 As shown, the input device 100 identifies the cross-sectional shape DK of the key device 301, which rotates in contact with the touch panel 200, and detects its rotation operation. The input device 100 detects the user's preference for rotating the key device 301 one full turn while the user is in contact with the touch panel 200. The user's preference refers to, for example,... Figure 13 As shown, it is a habit of rotating in three stages: R1, R2, and R3.

[0105] Furthermore, the input device 100 can also perform pre-defined actions based on the detected user's preferences.

[0106] Furthermore, the shape of the key device 301 is arbitrary. In this embodiment, such as... Figure 12 As shown, the key device 301 is generally rod-shaped, and its cross-sectional shape DK is a combination of a circle and a rectangle.

[0107] If the pressure detected by the pressure detection unit 120 at any contact point on the contact surface CS is greater than or equal to a predetermined value, the position detection unit 110 determines that the touch panel 200 is pressed by the key device 301 at that contact point. Furthermore, the position detection unit 110 defines the set of contact points determined to be pressed as a cross-sectional shape DK. The position detection unit 110 determines the cross-sectional shape DK formed by the key device 301 rotating on the touch panel 200 at fixed time intervals, such as clock intervals. At this time, the position detection unit 110 can also determine vector data representing the cross-sectional shape DK. In this case, the recording unit 130 can also record this vector data.

[0108] like Figure 1 As shown, the input device 100 may also include a recording unit 111. The recording unit 111 determines variables for recording the operation of the cross-sectional shape DK extracted by the position detection unit 110. In this case, the recording unit 111... Figure 5 After step S105, variables are determined for recording the operation of the cross-sectional shape DK extracted by the position detection unit 110.

[0109] exist Figure 13 In the example shown, rotation R1 is performed at the aforementioned fixed intervals, and the position detection unit 110 determines the i=0th cross-sectional shape DK0 and the i=1th cross-sectional shape DK1. The recording unit 111 determines the variables used to record the rotation R1 based on the cross-sectional shapes DK0 and DK1, namely the center coordinate C1 of the rotation, the rotation radius r1, and the rotation angle θ1. Thus, the recording unit 111 determines the variables to record the rotation each time the position detection unit 110 extracts the contact surface DK.

[0110] Then, the feature extraction unit 140 extracts data representing the rotational action of the operating body, i.e. the key device 301, from the history of the variables determined by the description unit 111.

[0111] Furthermore, even with the key device 301, the pressure distribution PD in the cross-sectional shape DK can be taken into account.

[0112] As described above, according to Embodiment 3, the input device 100 determines the set of contact points where pressure is detected to be greater than or equal to a predetermined value as the cross-sectional shape. Therefore, the input device 100 can identify the cross-sectional shape of the operating body, i.e., the key device 301, and in subsequent processing, can determine the operation of the key device 301 based on the identified cross-sectional shape.

[0113] (Implementation Method 4)

[0114] Next, Embodiment 4 of the present invention will be described. Structures and processes equivalent to those in Embodiments 1 to 3 will be labeled with the same reference numerals. In Embodiment 4, multiple input devices 100 cooperate with a server to perform processing.

[0115] In implementation method 4, by Figure 14 The input system 400 shown detects multiple input operations and performs processing corresponding to the detection results. The input system 400 includes a server 500 and one or more input devices 100, 101, 102 that can be communicatively connected to the server 500 via a computer communication network 600 such as the Internet.

[0116] Figure 14 The functional components shown are distributed among the server 500, input device 100, etc. For example, each of the input device 100 may have a position detection unit 110 and a pressure detection unit 120, and the server 500 may have a recording unit 130, a feature extraction unit 140, a comparison unit 150, a registration unit 160, and an execution unit 170.

[0117] The input system 400 described in this embodiment provides a service for online real estate sales contracts. Here, we envision a scenario where a real estate agent using input device 100 provides brokerage services for a real estate sales contract between seller "A" using input device 101 and buyer "B" using input device 102, and the seller and buyer exchange real estate sales contracts online.

[0118] like Figure 15 As shown, there are typically two real estate purchase and sale contracts: one for the seller (201) and one for the buyer (202). In both contracts 201 and 202, the seller's seal RS1 and the buyer's seal RS2 are affixed at predetermined locations. For example, there may be seals affixed across both contracts 201 and 202, or seals affixed after the seller's and buyer's signatures. In this embodiment, each seal RS1 and RS2 is an operable entity whose sliding characteristics should be extracted.

[0119] First, the registration unit 160 pre-registers data representing the sliding characteristics generated by the operating body for each input device 101, 102. Here, the registration unit 160 registers the cross-sectional shape of the operating body, i.e., the stamps RS1 and RS2, and the position where the stamps RS1 and RS2 should be affixed.

[0120] Then, the real estate agent uses the input unit 10 (described later, i.e., a camera) of the input device 100 to photograph the two real estate sales contracts 201 and 202, and uploads the images to the server 500. The server 500 then sends the images of the real estate sales contracts 201 and 202 to the seller's input device 101 and the buyer's input device 102. The input devices 101 and 102 each display the received images of the real estate sales contracts 201 and 202 on the display unit 20 (described later, i.e., the touch panel 200). Afterwards, the seller and buyer affix their seals RS1 and RS2 respectively to the touch panels 200 of their respective input devices 101 and 102.

[0121] The position detection unit 110 of each of the input devices 101 and 102 detects the position of the operating body sliding on the operating surface. Then, the pressure detection unit 120 of each of the input devices 101 and 102 detects the pressure of the operating body pressing against the operating surface at the detected position of the operating body. Here, the position detection unit 110 and the pressure detection unit 120 each extract the set of contact points pressed with a value greater than or equal to a predetermined value as the cross-sectional shape of stamps RS1 and RS2, and each detects the position where stamps RS1 and RS2 are affixed.

[0122] The recording unit 130 of the server 500 continuously acquires the position detected by the position detection unit 110 and the pressure generated by the operating body at that position, and records the history of the position and pressure of the operating body acquired for each input device 101 and 102. Here, the recording unit 130 acquires the cross-sectional shape and position of the stamps RS1 and RS2 extracted by the position detection unit 110 and the pressure detection unit 120, and records them for each input device 101 and 102.

[0123] The feature extraction unit 140 of the server 500 extracts data representing the sliding characteristics generated by the operating body from the history of the position and pressure of the operating body recorded by the recording unit 130 for each input device 101, 102. Here, since the stamping operation is a temporary operation, the feature extraction unit 140 extracts the cross-sectional shape and position of the stamps RS1 and RS2 respectively.

[0124] The comparison unit 150 of the server 500 compares the data representing the sliding characteristics generated by the operating body extracted for each input device 101, 102 with the data representing the sliding characteristics generated by the operating body pre-registered by the registration unit 160 for each input device 101, 102. Here, the comparison unit 150 compares whether the cross-sectional shape of the extracted stamps RS1, RS2 is consistent with the stamps RS1, RS2 registered in the registration unit 160, and whether they are stamped at the registered position.

[0125] The execution unit 170 of the server 500 executes a pre-defined action if the data representing the sliding characteristics generated by the operating body extracted from each input device 101, 102 matches the data representing the sliding characteristics generated by the operating body pre-registered for each input device. Here, if the comparison result shows that the cross-sectional shape of the extracted stamps RS1 and RS2 matches the registered cross-sectional shape and is affixed to the registered position, the execution unit 170 performs settlement and other processing for the real estate transaction.

[0126] Alternatively, the server 500 may only have a recording unit 130, while the input device 100 and other components may each have the remaining functional structural parts. Furthermore, as... Figure 16 As shown, the input system 400 may also not have a server 500. In this case, the input devices 100, 101, and 102 can also cooperate through peer-to-peer communication to detect multiple input operations and perform processing corresponding to the detection results.

[0127] As described above, according to Embodiment 4, the input system 400 receives operations performed by an operator from multiple input devices 100, and executes a pre-defined action corresponding to the characteristics of the received multiple operations. Therefore, effective utilization in various online scenarios is expected by utilizing operation information from multiple input devices 100, etc. Furthermore, interlocking functions can also be implemented.

[0128] (Variation Example 1)

[0129] In the above embodiment, the example described is the detection of a single input, such as handwriting pattern T2, contact surface CS, cross-sectional shape DK, and stamp RS1. However, the input device 100 and input system 400 can also detect multiple inputs simultaneously. For example, the input device 100 and input system 400 may... Figure 17As shown, the system can detect the pressing points PP1 and PP2, and detect the handwriting pattern T3. At this time, the position detection unit 110 and the pressure detection unit 120 detect multiple positions and the pressure at each position, the recording unit 130 records the data, and the feature extraction unit 140 extracts data representing the features of each input.

[0130] (Variation Example 2)

[0131] In the above embodiments, it is described that the input device 100 extracts data representing the sliding characteristics generated by the operating body 300 from the history of the position and pressure of the operating body 300, performs comparison, registration, and execution of the operation. However, the input device 100 may also extract a portion of the history for comparison operations, etc. For example, as in the stamping operation in Embodiment 4, the characteristic quantity of the time point at which the stamping operation is completed when the cross-sectional shape of the stamp RS1, etc., is completely detected can be used as data representing the sliding characteristics.

[0132] The embodiments 1 to 4 of the present invention have been described above, but the input devices 100, 101, 102, etc., and the server 500 involved in embodiments 1 to 4 are adopted. Figure 18 The hardware structure is as shown. That is, the input devices 100, 101, 102, etc., and the server 500 have an input unit 10, a display unit 20, a control unit 30, a main storage unit 40, an auxiliary storage unit 50, a clock unit 60, and a communication unit 70, which are connected to each other via a bus 80.

[0133] The input unit 10 includes a position input device such as a touchpad, a camera for capturing images or videos, a keyboard, etc.

[0134] The display unit 20 includes a liquid crystal display, an organic EL (Electro Luminescence) display, a static display surface where display content is fixed by printing or molding, such as printed material or multi-color molded rubber sheets, electronic paper, or a touch panel that integrates any of these with a touchpad. The touch panel is, for example, a capacitive touch panel.

[0135] The control unit 30 includes, for example, a CPU (Central Processing Unit) as an integrated circuit. By executing the program stored in the auxiliary storage unit 50, the control unit 30 performs the above-mentioned processing and realizes various functions of the input device 100 and the server 500.

[0136] The main storage unit 40 contains RAM (Random Access Memory). Programs are loaded into the main storage unit 40 from the secondary storage unit 50. Furthermore, the main storage unit 40 is used as the working area of ​​the control unit 30.

[0137] The auxiliary storage unit 50 includes non-volatile memory such as EEPROM (Electrically Erasable Programmable Read-Only Memory), SSD (Solid State Drive), and Hard Disk Drive. In addition to programs, the auxiliary storage unit 50 also stores various data used by the control unit 30 for processing. Following instructions from the control unit 30, the auxiliary storage unit 50 supplies data used by the control unit 30 to the control unit 30 and stores the data supplied from the control unit 30.

[0138] The clock unit 60 includes, for example, a crystal resonator, a silicon resonator, a crystal oscillator, and a clock generating circuit with other transmitting circuits. The clock unit 60 generates and outputs a clock signal based on the clock generated by the clock generating circuit. The clock signal includes clock pulses, and the control unit 30 counts the number of rises of the clock pulses using built-in hardware components or executed software processing to keep track of time.

[0139] The communication unit 70 includes a network interface circuit for transmitting and receiving Ethernet frames with external devices. The communication unit 70 receives signals from the outside and outputs the data represented by those signals to the control unit 30. Additionally, the communication unit 70 transmits signals representing the data output from the control unit 30 to external devices.

[0140] Furthermore, the input unit 10 and the display unit 20 may also be configured to be separate from the input device 100. For example, the input unit 10 and the display unit 20 may be connected to the input device 100 from the control box of the input device 100 via an extension cable or the like.

[0141] Furthermore, the functions of input device 100 and server 500 can also be implemented through dedicated hardware or a conventional computer system.

[0142] For example, by distributing the program executed by the control unit 30 to a computer-readable, non-transitory recording medium and installing the program into a computer, an apparatus for performing the above-described processing can be constructed. Examples of such recording media include floppy disks, CD-ROMs (Compact Disc Read-Only Memory), DVDs (Digital Versatile Discs), and MOs (Magneto-Optical Discs).

[0143] Alternatively, the program can be pre-stored on a disk device of a server on a communication network such as the Internet, for example, superimposed on a carrier wave, and downloaded to a computer.

[0144] Alternatively, the above process can also be achieved by forwarding the program through a communication network and initiating its execution.

[0145] Furthermore, the aforementioned processing can also be achieved by executing all or part of the program on a server device, and by sending and receiving information related to the processing and executing the program via a communication network.

[0146] Furthermore, when the above functions are implemented by the OS (Operating System) or through the coordinated action of the OS and applications, only the parts outside the OS can be stored on the medium for distribution, or they can be downloaded to a computer.

[0147] Furthermore, the means of realizing the functions of the input device 100 and the server 500 are not limited to software; some or all of them can also be realized through dedicated hardware containing circuits.

[0148] This invention can be implemented and modified in various ways without departing from its broad spirit and scope. Furthermore, the above-described embodiments are for illustrative purposes only and do not limit the scope of the invention. That is, the scope of the invention is defined by the claims, not the embodiments. Moreover, various modifications implemented within the scope of the claims and their equivalents are considered to fall within the scope of this invention.

[0149] Explanation of the label

[0150] 10 Input Unit, 20 Display Unit, 30 Control Unit, 40 Main Storage Unit, 50 Auxiliary Storage Unit, 60 Clock Unit, 70 Communication Unit, 80 Bus, 100, 101, 102 Input Device, 110 Position Detection Unit, 111 Recording Unit, 120 Press Detection Unit, 130 Recording Unit, 140 Feature Extraction Unit, 150 Comparison Unit, 160 Registration Unit, 170 Execution Unit, 131 Calculation Unit, 200 Touch Panel, 201, 202 Real Estate Purchase and Sale Contract, 300 Operating Body, User's Finger, 301 Key Device, 400 Input System, 500 Server, 600 Computer Communication Network, A, A', B, B', C, C'O Intersection Point, CS Contact Surface, C1 Center Coordinates, DK, DK0, DK1 Profile shape, F1, F2, F3, F4, F5, F6 feature points, G geometric centroid, PD pressure distribution, P O Highest pressure point, RS1, RS2 stamps, R1, R2, R3 rotation, r1 rotation radius, TO, T1, T2 handwriting pattern, θ slope, θ1 rotation angle

Claims

1. An input device comprising: The position detection unit detects the position of the operating body that slides on the operating surface; The pressure detection unit detects the pressure of the operating body pressing the operating surface at the position detected by the position detection unit. The recording unit obtains the position of the operating body from the position detection unit, obtains the pressure generated by the operating body at the position from the pressure detection unit, and records their history; and The feature extraction unit extracts the sliding feature quantities generated by the operating body from the position and pressure history of the operating body recorded by the recording unit, and determines feature points on the handwriting based on the changes in position and pressure over time detected when the operating body is in contact with the operating surface. The position detection unit also extracts the contact surface between the operating body and the operating surface. The pressure detection unit also detects the pressure distribution on the contact surface extracted by the position detection unit. The recording unit also records the history of the pressure distribution on the contact surface detected by the pressure detection unit. The feature extraction unit extracts feature quantities from the pressure distribution history recorded by the recording unit on the contact surface. The input device also includes a calculation unit that calculates an approximate pressure gradient based on the pressure distribution on the contact surface extracted by the position detection unit. The recording unit records the history of the pressure gradient calculated by the calculation unit. The feature extraction unit extracts feature quantities from the pressure gradient history recorded by the recording unit. The pressure gradient is composed of multiple slopes connecting adjacent points on a plurality of points on an evaluation surface that cuts the pressure distribution. The evaluation surface is the surface that passes through the geometric centroid and the point of highest pressure of the contact surface. The junction is the intersection of the evaluation surface with a pre-defined isobaric line of one or more.

2. The input device according to claim 1, further comprising: The registration department, which pre-registers the feature values ​​of the feature points of the handwriting generated by the operating body; and The comparison unit compares the feature values ​​of the handwriting points extracted by the feature extraction unit from the handwriting generated by the operating body with the pre-registered feature values ​​of the handwriting points generated by the operating body. The registration department also registers the characteristic quantities of the pressure distribution history in the contact surface generated by the operating body. The comparison unit further compares the feature quantities of the pressure distribution history extracted by the feature extraction unit with the feature quantities of the registered pressure distribution history in the contact surface. The registration department also registers characteristic quantities of the pressure gradient history that approximates the pressure distribution in the contact surface. The comparison unit also compares the characteristic quantities of the pressure gradient history recorded by the recording unit with the characteristic quantities of the registered pressure gradient history.

3. The input device according to claim 1 or 2, wherein, The feature extraction unit processes the position and pressure recorded by the recording unit using a predefined function, and determines the points that meet the pre-set conditions as feature points on the handwriting. The recording unit also records the feature values ​​of the feature points determined by the feature extraction unit.

4. The input device according to claim 3, wherein, The feature extraction unit determines the location of the position as a feature point by performing a second-order derivative of the position and pressure history of the operating body recorded by the recording unit over time and obtaining a value that satisfies a predetermined condition.

5. The input device according to claim 3, wherein, The recording unit records the time-varying rate of change of the detected position and pressure as a feature quantity of the feature point determined by the feature extraction unit.

6. The input device according to claim 3, wherein, The recording unit records the values ​​obtained by performing second-order differentiation on the detected position and pressure as feature quantities of the feature points determined by the feature extraction unit.

7. The input device according to claim 3, further comprising: The registration department, which pre-registers the feature points of the handwriting generated by the operating body and the feature quantities of those feature points; and The comparison unit compares the feature values ​​of the feature points determined by the feature extraction unit with the feature values ​​of the feature points registered in the registration unit.

8. The input device according to claim 7, further comprising: The execution unit performs pre-defined processing when the comparison unit determines that the feature quantity of the feature point determined by the feature extraction unit is consistent with the feature quantity of the feature point pre-registered in the registration unit.

9. The input device according to claim 1 or 2, wherein, The position detection unit determines that the operating surface is pressed by the operating body at the contact point where the pressure detected by the pressure detection unit is greater than or equal to a predetermined value, and determines the set of contact points determined to be pressed as information representing the cross-sectional shape of the operating body.

10. The input device according to claim 1 or 2, wherein, The position detection unit and the pressure detection unit are integrated into one unit. The pressure detection unit detects the pressure generated by the operating body while the position detection unit detects the position of the operating body.

11. An input system comprising a server and one or more input devices communicatively connected to said server. Through the server, and the input device (or one or more input devices). The position of the operating body sliding on the operating surface is detected. The pressure applied by the operating body to the operating surface at the detected location is measured. The detected position of the operating body and the pressure generated by the operating body at that position are obtained, and the history of the obtained position and pressure of the operating body is recorded for each of the input devices. Based on the changes in position and pressure over time detected by each input device while the operating body is in contact with the operating surface, feature points on the handwriting are determined. Data representing feature points on the handwriting determined for each of the input devices is pre-registered. The data representing feature points on the handwriting determined for each of the input devices is compared with the data representing feature points on the handwriting pre-registered for each of the input devices. If the comparison result shows that the data representing the features generated by the operating body extracted for each of the input devices matches the data representing the sliding features generated by the operating body pre-registered for each of the input devices, a pre-defined action is performed. Further extract the contact surface between the operating body and the operating surface. The pressure distribution in the extracted contact surface is further detected. The history of the pressure distribution in the detected contact surface is further recorded. From the recorded history of pressure distribution on the contact surface, extract the characteristic quantities of the pressure distribution history on the contact surface. Calculate an approximate pressure gradient for the pressure distribution in the extracted contact surface. The history of the calculated pressure gradient is recorded. From the recorded history of the pressure gradient, extract the feature quantities of the pressure gradient history. The pressure gradient is composed of multiple slopes connecting adjacent points on a plurality of points on an evaluation surface that cuts the pressure distribution. The evaluation surface is the surface that passes through the geometric centroid and the point of highest pressure of the contact surface. The junction is the intersection of the evaluation surface with a pre-defined isobaric line of one or more.

12. An input system having multiple input devices that cooperate in operation. The position of the operating body sliding on the operating surface is detected. The pressure applied by the operating body to the operating surface at the detected location is measured. The detected position of the operating body and the pressure generated by the operating body at that position are obtained, and the history of the obtained position and pressure of the operating body is recorded for each of the input devices. Based on the changes in position and pressure detected by each of the input devices when the operating body is in contact with the operating surface, feature points on the handwriting are determined. Data representing feature points on the handwriting determined for each of the input devices is pre-registered. The data representing feature points on the handwriting determined for each of the input devices is compared with the data representing feature points on the handwriting pre-registered for each of the input devices. If the comparison result shows that the data representing the features generated by the operating body extracted for each of the input devices matches the data representing the sliding features generated by the operating body pre-registered for each of the input devices, a pre-defined action is performed. Further extract the contact surface between the operating body and the operating surface. The pressure distribution in the extracted contact surface is further detected. The history of the pressure distribution in the detected contact surface is further recorded. From the recorded history of pressure distribution on the contact surface, extract the characteristic quantities of the pressure distribution history on the contact surface. Calculate an approximate pressure gradient for the pressure distribution in the extracted contact surface. The history of the calculated pressure gradient is recorded. From the recorded history of the pressure gradient, extract the feature quantities of the pressure gradient history. The pressure gradient is composed of multiple slopes connecting adjacent points on a plurality of points on an evaluation surface that cuts the pressure distribution. The evaluation surface is the surface that passes through the geometric centroid and the point of highest pressure of the contact surface. The junction is the intersection of the evaluation surface with a pre-defined isobaric line of one or more.

13. An input method, wherein, The computer performs the following processing: The detection position of the operating body sliding on the operating surface and the detection pressure when the operating body presses against the operating surface at that detection position are obtained. The history of the detection position and detection pressure of the obtained operating body is recorded. From the recorded history of the detection position and detection pressure of the manipulator, the characteristic quantities of the sliding generated by the manipulator are extracted. Based on the changes in position and pressure over time detected when the operating body is in contact with the operating surface, feature points on the handwriting are determined. Further extract the contact surface between the operating body and the operating surface. The pressure distribution in the extracted contact surface is further detected. The history of the pressure distribution in the detected contact surface is further recorded. From the recorded history of pressure distribution on the contact surface, extract the characteristic quantities of the pressure distribution history on the contact surface. Calculate an approximate pressure gradient for the pressure distribution in the extracted contact surface. The history of the calculated pressure gradient is recorded. From the recorded history of the pressure gradient, extract the feature quantities of the pressure gradient history. The pressure gradient is composed of multiple slopes connecting adjacent points on a plurality of points on an evaluation surface that cuts the pressure distribution. The evaluation surface is the surface that passes through the geometric centroid and the point of highest pressure of the contact surface. The junction is the intersection of the evaluation surface with a pre-defined isobaric line of one or more.

14. A recording medium that stores a computer-readable, non-transitory recording medium containing a program that causes a computer to perform the following processes: The detection position of the operating body sliding on the operating surface and the detection pressure when the operating body presses against the operating surface at that detection position are obtained. The history of the detection position and detection pressure of the obtained operating body is recorded. From the recorded history of the detection position and detection pressure of the manipulator, the characteristic quantities of the sliding generated by the manipulator are extracted. Based on the changes in position and pressure over time detected when the operating body is in contact with the operating surface, feature points on the handwriting are determined. Further extract the contact surface between the operating body and the operating surface. The pressure distribution in the extracted contact surface is further detected. The history of the pressure distribution in the detected contact surface is further recorded. From the recorded history of pressure distribution on the contact surface, extract the characteristic quantities of the pressure distribution history on the contact surface. Calculate an approximate pressure gradient for the pressure distribution in the extracted contact surface. The history of the calculated pressure gradient is recorded. From the recorded history of the pressure gradient, extract the feature quantities of the pressure gradient history. The pressure gradient is composed of multiple slopes connecting adjacent points on a plurality of points on an evaluation surface that cuts the pressure distribution. The evaluation surface is the surface that passes through the geometric centroid and the point of highest pressure of the contact surface. The junction is the intersection of the evaluation surface with a pre-defined isobaric line of one or more.

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