Human body 3D situation virtual sand table display control method and sand table display system

Abstract

The invention discloses a human body 3D situation virtual sand table display control method and a sand table display system, and relates to the technical field of man-machine interaction input. The method comprises the following steps: extracting a detection angle of a joint part at each acquisition moment and a detection length of a limb part at the end part of the joint; dividing the limb part into a rigid limb part and a flexible limb part according to the detection lengths of the limb part at the plurality of collection moments; for each rigid limb part, obtaining a standard length range of the rigid limb part according to the detection length of each acquisition moment; for each flexible limb part, obtaining a standard length range of the flexible limb part according to the detection angle and the detection length of the joint part at each collection moment; and judging whether the detection length of each limb part at the current moment accords with the corresponding standard length range or not. According to the method, situation display errors caused by human body 3D scanning data acquisition errors are effectively avoided, and the man-machine interaction accuracy of situation display is improved.

Claims

1. A human body 3D situation virtual sand table display control method, characterized in that: include, Extract the detection angle of the joint part and the detection length of the limb part at the end of the joint at each acquisition moment; The limb parts are divided into rigid limb parts and flexible limb parts according to the detected lengths of the limb parts at multiple acquisition moments; For each rigid limb part, the standard length range of the rigid limb part is obtained according to the detected length at each acquisition moment; For each flexible limb part, the standard length range of the flexible limb part is obtained according to the detection angle and detection length of the joint part at each acquisition moment; Determine whether the detected length of each limb part at the current moment meets the corresponding standard length range; If yes, the detection angle of the joint part and the detection length of the limb part at the end of the joint at the current moment are used as the data source for 3D display of the human body; If not, the corrected data is selected within the standard length range as the data source for 3D display of the human body.

2. The method according to claim 1, characterized in that The step of dividing the limb parts into rigid limb parts and flexible limb parts according to the detected lengths of the limb parts at multiple acquisition moments, include, According to the detection length of each limb part at multiple collection moments, the maximum detection length and the minimum detection length of each limb part at different collection moments are obtained; The ratio of the difference between the maximum detection length and the minimum detection length of the limb parts at different acquisition moments to the maximum detection length is taken as the detection quantitative variation amplitude of the limb parts; The detected variable amplitudes of each limb part are sorted according to the numerical value, and the mean of the difference between each detected variable amplitude and the adjacent detected variable amplitudes is calculated as the discrimination limit; The limb part corresponding to the detection amount variation amplitude whose difference with the adjacent detection amount variation amplitudes in the sorting order is less than the distinction limit is regarded as the rigid limb part; The limb part corresponding to the detection amount variation amplitude whose difference between the detection amount variation amplitudes of adjacent arranged ones is greater than the said distinction limit is taken as the flexible limb part.

3. The method according to claim 1, characterized in that The step of obtaining the standard length range of the rigid limb part according to the detected length at each acquisition moment, include, For each rigid limb part, perform the following steps separately, Calculate and obtain a reference value of the detection length at all acquisition moments, wherein the reference value includes a median; The detection lengths at each acquisition moment are sorted according to the numerical value, and the average of the difference between each detection length and the sorted adjacent detection length is calculated as the adjacent step length; Starting from the reference value, sequentially along the increasing and decreasing directions of the values ​​of the detection lengths, calculate one by one whether the difference between two adjacent detection lengths is less than the adjacent step length; If so, continue calculating; If not, the numerical distribution range of the detected length included in the calculation will be used as the standard length range of the rigid limb part.

4. The method according to claim 1, characterized in that: The step of obtaining the standard length range of the flexible limb part according to the detection angle and detection length of the joint part at each acquisition moment, include, For each flexible limb part, perform the following steps separately, Acquire a plurality of joint parts at the end of the flexible limb part, which together constitute the associated part where the flexible limb part is located; Calculate and obtain the difference in the detection length of the flexible limb part between different acquisition moments and the cumulative value of the difference in the detection angle of several joint parts as the morphological difference of the associated part between different acquisition moments; According to the morphological differences of the associated parts at different collection times, the collection times with the same morphology of the associated parts are divided into the same collection time set; For each collection time set, the numerical distribution range of the detection angles of several joints at the end of the flexible limb part is obtained, and the numerical distribution range of the detection length of the flexible limb part is used as the standard length range.

5. The method according to claim 4, characterized in that The step of classifying the acquisition moments with the same morphology of the associated parts into the same acquisition moment set according to the morphological differences of the associated parts at different acquisition moments includes: Selecting a number of the collection moments from among all the collection moments as marked collection moments; Calculate and obtain the morphological difference between each marked acquisition moment and other acquisition moments; The other collection moments other than each marked collection moment and the marked collection moment with the smallest morphological difference are divided into the same collection moment set; In each collection time set, the cumulative value of the morphological difference between each collection time and all other collection times is calculated; Determine whether the collection time with the smallest cumulative value of morphological differences with all other collection times in each collection time set is the marked collection time; If so, a collection time set with consistent morphology of associated parts is obtained; If not, then reselect the marked collection time, and re-divide the collection time set to judge the consistency of the associated part morphology, until a collection time set with consistent associated part morphology is obtained.

6. The method according to claim 5, characterized in that The step of reselecting the mark collection time includes: The collection time with the smallest cumulative value of morphological differences with all other collection times in each collection time set is used as the reselected marked collection time.

7. The method according to claim 1 or 4, characterized in that: The step of judging whether the detected length of each limb part at the current moment meets the corresponding standard length range, include, For each flexible limb part, perform the following steps separately, A collection time set that meets the corresponding standard length range is selected according to the detection length of the flexible limb part at the current moment and the detection angles of several joint parts at the end of the flexible limb part; Determine whether the detected length of the flexible limb part at the current moment falls within the standard length range of the collection moment set; If yes, it is determined that the detected length of the flexible limb part meets the corresponding standard length range; If not, then vice versa.

8. The method according to claim 1 or 4, characterized in that: The step of selecting the corrected data within the standard length range as the data source for 3D display of the human body, include, For rigid limb parts, the median of their standard length range was used as the corrected data; For flexible limb parts, the median of the numerical distribution range of the detected length of the flexible limb part at each collection moment contained in the collection moment set that meets the corresponding standard length range at the current moment is used as the corrected data.

9. A human body 3D situation virtual sand table display control method, characterized in that: include, Receiving a human body 3D display data source in a human body 3D situation virtual sandbox display control method according to any one of claims 1 to 8; The human body 3D display data source is displayed in a virtual sandbox.

10. A human body 3D situation virtual sand table display system, characterized in that: include, Motion capture sensor, used to collect 3D scanning data of the human body; A verification unit, used to extract the detection angle of the joint part and the detection length of the limb part at the joint end at each acquisition moment; The limb parts are divided into rigid limb parts and flexible limb parts according to the detected lengths of the limb parts at multiple acquisition moments; For each rigid limb part, the standard length range of the rigid limb part is obtained according to the detected length at each acquisition moment; For each flexible limb part, the standard length range of the flexible limb part is obtained according to the detection angle and detection length of the joint part at each acquisition moment; Determine whether the detected length of each limb part at the current moment meets the corresponding standard length range; If yes, the detection angle of the joint part and the detection length of the limb part at the end of the joint at the current moment are used as the data source for 3D display of the human body; If not, the corrected data is selected within the standard length range as the data source for 3D display of the human body; A display unit, used for receiving a data source for a 3D display of a human body; The human body 3D display data source is displayed in a virtual sandbox.

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