find_planar_uncalib_deformable_modelT_find_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model (Operator)

Name

find_planar_uncalib_deformable_modelT_find_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model — Find the best matches of a planar projective invariant deformable model in an image.

Signature

Description

The operator find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model finds the best NumMatchesNumMatchesNumMatchesNumMatchesnumMatchesnum_matches instances of the perspectively distorted deformable model ModelIDModelIDModelIDModelIDmodelIDmodel_id in the input image ImageImageImageImageimageimage. The model must have been created previously by calling create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model or read_deformable_modelread_deformable_modelReadDeformableModelReadDeformableModelReadDeformableModelread_deformable_model.

HomMat2DHomMat2DHomMat2DHomMat2DhomMat2Dhom_mat_2d determines the projective transformation (homography), which describes the position of the found matches. In case several objects are found, the different homographies are concatenated. Then, a single homography can be extracted using tuple_select_range(HomMat2D,Index*9,(Index+1)*9-1, SelectedHomMat2D)tuple_select_range(HomMat2D,Index*9,(Index+1)*9-1, SelectedHomMat2D)TupleSelectRange(HomMat2D,Index*9,(Index+1)*9-1, SelectedHomMat2D)TupleSelectRange(HomMat2D,Index*9,(Index+1)*9-1, SelectedHomMat2D)TupleSelectRange(HomMat2D,Index*9,(Index+1)*9-1, SelectedHomMat2D)tuple_select_range(HomMat2D,Index*9,(Index+1)*9-1, SelectedHomMat2D). The different results are sorted according to their ScoreScoreScoreScorescorescore in descending order.

The row and column coordinates of the origin of the deformable model within the search image can be determined calling projective_trans_pixel(HomMat2D,0,0,Row,Column)projective_trans_pixel(HomMat2D,0,0,Row,Column)ProjectiveTransPixel(HomMat2D,0,0,Row,Column)ProjectiveTransPixel(HomMat2D,0,0,Row,Column)ProjectiveTransPixel(HomMat2D,0,0,Row,Column)projective_trans_pixel(HomMat2D,0,0,Row,Column). Usually the origin of the model is the center of gravity of the image region used to create the deformable model calling create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model. The origin can be modified using set_deformable_model_originset_deformable_model_originSetDeformableModelOriginSetDeformableModelOriginSetDeformableModelOriginset_deformable_model_origin.

The model contours of found instances can be visualized using projective_trans_contour_xldprojective_trans_contour_xldProjectiveTransContourXldProjectiveTransContourXldProjectiveTransContourXldprojective_trans_contour_xld with the HomMat2DHomMat2DHomMat2DHomMat2DhomMat2Dhom_mat_2d and the original model contour, which has been extracted previously using get_deformable_model_contoursget_deformable_model_contoursGetDeformableModelContoursGetDeformableModelContoursGetDeformableModelContoursget_deformable_model_contours.

The ScoreScoreScoreScorescorescore is a number between 0 and 1 and may indicate how much of the model is visible within the image.

Example: Half of the model is occluded in the search image. As a result, the ScoreScoreScoreScorescorescore of this match can not exceed 0.5.

Input parameters in detail

ImageImageImageImageimageimage and its domain:

The domain of the image ImageImageImageImageimageimage determines the search space for the reference point of the model, i.e., for the center of gravity of the domain (region) of the image that was used to create the deformable model with create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model. A different origin set with set_deformable_model_originset_deformable_model_originSetDeformableModelOriginSetDeformableModelOriginSetDeformableModelOriginset_deformable_model_origin is not taken into account. The model is searched within those points of the domain of the image, in which the model lies completely within the image. This means that the model will not be found if it extends beyond the borders of the image, even if it would achieve a score greater than MinScoreMinScoreMinScoreMinScoreminScoremin_score (see below). Note that, if for a certain pyramid level the model touches the image border, it might not be found even if it lies completely within the original image. As a rule of thumb, the model might not be found if its distance to an image border falls below . This behavior can be changed with set_system('border_shape_models','true')set_system("border_shape_models","true")SetSystem("border_shape_models","true")SetSystem("border_shape_models","true")SetSystem("border_shape_models","true")set_system("border_shape_models","true"), which will cause models that extend beyond the image border to be found if they achieve a score greater than MinScoreMinScoreMinScoreMinScoreminScoremin_score. Here, points lying outside the image are regarded as being occluded, i.e., they lower the score. It should be noted that the runtime of the search will increase in this mode. Note further, that in rare cases, which occur typically only for artificial images, the model might not be found also if for certain pyramid levels the model touches the border of the reduced domain. Then, it may help to enlarge the reduced domain by using, e.g., dilation_circledilation_circleDilationCircleDilationCircleDilationCircledilation_circle.

Angle and Scale parameters:

The parameters AngleStartAngleStartAngleStartAngleStartangleStartangle_start, AngleExtentAngleExtentAngleExtentAngleExtentangleExtentangle_extent, ScaleRMinScaleRMinScaleRMinScaleRMinscaleRMinscale_rmin, ScaleRMaxScaleRMaxScaleRMaxScaleRMaxscaleRMaxscale_rmax, ScaleCMinScaleCMinScaleCMinScaleCMinscaleCMinscale_cmin and ScaleCMaxScaleCMaxScaleCMaxScaleCMaxscaleCMaxscale_cmax are used to specify a basic range of up to an anisotropic transformation that is exhaustively searched on the top level of the image pyramid. The parameters AngleStartAngleStartAngleStartAngleStartangleStartangle_start and AngleExtentAngleExtentAngleExtentAngleExtentangleExtentangle_extent determine the range of possible rotations in which the model is exhaustively searched. ScaleRMinScaleRMinScaleRMinScaleRMinscaleRMinscale_rmin, ScaleRMaxScaleRMaxScaleRMaxScaleRMaxscaleRMaxscale_rmax, ScaleCMinScaleCMinScaleCMinScaleCMinscaleCMinscale_cmin, and ScaleCMaxScaleCMaxScaleCMaxScaleCMaxscaleCMaxscale_cmax determine the range of possible anisotropic scales that are exhaustively searched in the image. A scale of 1 in both scale factors corresponds to the original size of the model.

The operator find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model may find objects outside this range, e.g., when the object is perspectively distorted. Hence, the range parameters are a kind of suggestion for the search algorithm. Starting from this, certain models in a wider range of transformations can be detected, depending on the used pyramid levels, but also on the model/image content. It is important to note that, e.g., small scale changes can be tolerated without the need to specify a scale range, leading to faster execution times.

Often, it is not necessary to use an anisotropic scaling to find the object on the top level of the pyramid. In these cases, ScaleCMinScaleCMinScaleCMinScaleCMinscaleCMinscale_cmin and ScaleCMaxScaleCMaxScaleCMaxScaleCMaxscaleCMaxscale_cmax should be set to 1. The search is then performed with isotropic scaling only, which is much faster. If the object should be detected despite severe perspective distortions anisotropic scaling is required. Here, ScaleRMinScaleRMinScaleRMinScaleRMinscaleRMinscale_rmin and ScaleRMaxScaleRMaxScaleRMaxScaleRMaxscaleRMaxscale_rmax specify the anisotropic scaling in row, ScaleCMinScaleCMinScaleCMinScaleCMinscaleCMinscale_cmin and ScaleCMaxScaleCMaxScaleCMaxScaleCMaxscaleCMaxscale_cmax in column direction.

Note that the transformations are treated internally such that the scalings are applied first, followed by the rotation. Therefore, the model should usually be aligned such that it appears horizontally or vertically in the model image.

Additionally, the operator find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model processes the parameters 'angle_step', 'scale_r_step' and 'scale_c_step' which can be set with the operator create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model or, as described below, with the generic parameters GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name and GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value. In most cases, the values that can be determined automatically by create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model lead to good results.

The parameter 'angle_step' determines the step size within the selected range of angles. 'angle_step' should be chosen based on the size of the object. Smaller models do not have many different discrete rotations in the image, and hence 'angle_step' should be chosen larger for smaller models. If AngleExtentAngleExtentAngleExtentAngleExtentangleExtentangle_extent is not an integer multiple of 'angle_step', 'angle_step' is modified accordingly. The parameters 'scale_r_step' and 'scale_c_step' determine the step size within the selected range of scales. Like 'angle_step', 'scale_r_step' and 'scale_c_step' should be chosen based on the size of the object. If the respective range of scales is not an integer multiple of 'scale_r_step' and 'scale_c_step', 'scale_r_step' and 'scale_c_step' are modified accordingly.

MinScoreMinScoreMinScoreMinScoreminScoremin_score:

The parameter MinScoreMinScoreMinScoreMinScoreminScoremin_score determines what score a potential match must at least have to be regarded as an instance of the model in the image. The larger MinScoreMinScoreMinScoreMinScoreminScoremin_score is chosen, the faster the search is. If the model can be expected never to be occluded in the images, MinScoreMinScoreMinScoreMinScoreminScoremin_score may be set as high as 0.8 or even 0.9.

NumMatchesNumMatchesNumMatchesNumMatchesnumMatchesnum_matches:

The maximum number of instances to be found can be determined with NumMatchesNumMatchesNumMatchesNumMatchesnumMatchesnum_matches. If more than NumMatchesNumMatchesNumMatchesNumMatchesnumMatchesnum_matches instances with a score greater than MinScoreMinScoreMinScoreMinScoreminScoremin_score are found in the image, only the best NumMatchesNumMatchesNumMatchesNumMatchesnumMatchesnum_matches instances are returned. If fewer than NumMatchesNumMatchesNumMatchesNumMatchesnumMatchesnum_matches are found, only that number is returned, i.e., the parameter MinScoreMinScoreMinScoreMinScoreminScoremin_score takes precedence over NumMatchesNumMatchesNumMatchesNumMatchesnumMatchesnum_matches. If all model instances exceeding MinScoreMinScoreMinScoreMinScoreminScoremin_score in the image should be found, NumMatchesNumMatchesNumMatchesNumMatchesnumMatchesnum_matches must be set to 0. In rare cases, NumMatchesNumMatchesNumMatchesNumMatchesnumMatchesnum_matches must be set to a higher value than the required number of matches. This is the case if, for instance, a small MinScoreMinScoreMinScoreMinScoreminScoremin_score is set.

When tracking the matches through the image pyramid, on each level, some less promising matches are rejected based on NumMatchesNumMatchesNumMatchesNumMatchesnumMatchesnum_matches. Thus, it is possible that some matches are rejected that would have had a higher score on the lowest pyramid level. Due to this, for example, the found match for NumMatchesNumMatchesNumMatchesNumMatchesnumMatchesnum_matches set to 1 might be different from the match with the highest score returned when setting NumMatchesNumMatchesNumMatchesNumMatchesnumMatchesnum_matches to 0 or > 1.

If multiple objects with a similar score are expected, but only the one with the highest score should be returned, it might be preferable to raise NumMatchesNumMatchesNumMatchesNumMatchesnumMatchesnum_matches, and then select the match with the highest score.

MaxOverlapMaxOverlapMaxOverlapMaxOverlapmaxOverlapmax_overlap:

If the model exhibits symmetries it may happen that multiple instances with similar positions but different rotations are found in the image. The parameter MaxOverlapMaxOverlapMaxOverlapMaxOverlapmaxOverlapmax_overlap determines by what fraction (i.e., a number between 0 and 1) two instances may at most overlap in order to consider them as different instances, and hence to be returned separately. If two instances overlap each other by more than MaxOverlapMaxOverlapMaxOverlapMaxOverlapmaxOverlapmax_overlap only the best instance is returned. The calculation of the overlap is based on the smallest enclosing rectangle of arbitrary orientation (see smallest_rectangle2smallest_rectangle2SmallestRectangle2SmallestRectangle2SmallestRectangle2smallest_rectangle2) of the found instances. If MaxOverlapMaxOverlapMaxOverlapMaxOverlapmaxOverlapmax_overlap=0, the found instances may not overlap at all, while for MaxOverlapMaxOverlapMaxOverlapMaxOverlapmaxOverlapmax_overlap=1 all instances are returned.

GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name, GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value:

With the generic parameters GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name and GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value it is possible to adjust parameters that typically do not have to be set by the user. By default the pose is extracted with high subpixel accuracy ('least_squares_very_high'"least_squares_very_high""least_squares_very_high""least_squares_very_high""least_squares_very_high""least_squares_very_high") through a least-squares adjustment, i.e., by minimizing the distances of the model points to their corresponding image points. However, if no high accuracy is required by an application, the subpixel precise extraction can be reduced or switched off as it increases the processing time. Here, 'subpixel' must be passed in GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name and 'none'"none""none""none""none""none", 'least_squares'"least_squares""least_squares""least_squares""least_squares""least_squares", 'least_squares_high'"least_squares_high""least_squares_high""least_squares_high""least_squares_high""least_squares_high" for GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value. A further use of GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name and GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value is to override the discretization steps of the search space 'angle_step', 'scale_r_step' and 'scale_c_step' that have been defined when the model was created in create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model.

As described in create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model the deformable matching algorithm searches exhaustively a basic set of parameters that are specified with AngleStartAngleStartAngleStartAngleStartangleStartangle_start,AngleExtentAngleExtentAngleExtentAngleExtentangleExtentangle_extent, ScaleRMinScaleRMinScaleRMinScaleRMinscaleRMinscale_rmin,ScaleRMaxScaleRMaxScaleRMaxScaleRMaxscaleRMaxscale_rmax,ScaleCMinScaleCMinScaleCMinScaleCMinscaleCMinscale_cmin and ScaleCMaxScaleCMaxScaleCMaxScaleCMaxscaleCMaxscale_cmax. However, to allow a detection even when the object is imaged under perspective distortion, an additional transformation is estimated. This additional transformation transforms the model from the original search range to a bigger perspectively distorted one. By allowing perspective distortions, the risk of false positives is also increased. One possible use of the parameter GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name is to help discarding false positives that occur, if for instance a small score was specified in MinScoreMinScoreMinScoreMinScoreminScoremin_score and the image contains significant clutter with similar shape as the model.

To restrict arbitrary perspective matches from occurring, the values 'angle_change_restriction'"angle_change_restriction""angle_change_restriction""angle_change_restriction""angle_change_restriction""angle_change_restriction" and 'aniso_scale_change_restriction'"aniso_scale_change_restriction""aniso_scale_change_restriction""aniso_scale_change_restriction""aniso_scale_change_restriction""aniso_scale_change_restriction" can be used in GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name. With 'angle_change_restriction'"angle_change_restriction""angle_change_restriction""angle_change_restriction""angle_change_restriction""angle_change_restriction" the maximal tolerated angular distortion can be restricted. As default value is set, which allows arbitrary distortion. By setting 'angle_change_restriction'"angle_change_restriction""angle_change_restriction""angle_change_restriction""angle_change_restriction""angle_change_restriction" to 0, no distortion is allowed at all. The set value should be within the interval [0, ]. This parameter tests, if the angle of 90 degree at the corners of the axis-aligned rectangle around the model points is changed by more than the corresponding GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value for the found instance of the model. Note that this parameter helps to restrict both affine (a shear mapping) and perspective parts of the transformation. As an example, with 'angle_change_restriction'"angle_change_restriction""angle_change_restriction""angle_change_restriction""angle_change_restriction""angle_change_restriction" a square-like model can be prevented to match with a parallelogram or an arbitrary trapezium.

With the parameter 'aniso_scale_change_restriction'"aniso_scale_change_restriction""aniso_scale_change_restriction""aniso_scale_change_restriction""aniso_scale_change_restriction""aniso_scale_change_restriction" the ratio of anisotropic scaling can be restricted (the smaller scale factor divided by the bigger scale factor). The value of this parameter ranges from the default value 0.0, where arbitrary distortion is allowed, to 1.0, where no distortion is allowed. One typical use for this parameter is to restrict for instance a square-like model to deform to a rectangular model.

NumLevelsNumLevelsNumLevelsNumLevelsnumLevelsnum_levels:

The number of pyramid levels used during the search is determined with NumLevelsNumLevelsNumLevelsNumLevelsnumLevelsnum_levels. If necessary, the number of levels is clipped to the range given when the deformable model was created with create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model. If NumLevelsNumLevelsNumLevelsNumLevelsnumLevelsnum_levels is set to 0, the number of pyramid levels specified in create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model is used.

GreedinessGreedinessGreedinessGreedinessgreedinessgreediness:

The parameter GreedinessGreedinessGreedinessGreedinessgreedinessgreediness determines how “greedily” the search should be carried out. If GreedinessGreedinessGreedinessGreedinessgreedinessgreediness=0, a safe search heuristic is used, which finds the model if it is visible in the image and the other parameters are set appropriately. However, the search will be relatively time consuming in this case. If GreedinessGreedinessGreedinessGreedinessgreedinessgreediness=1, an unsafe search heuristic is used, which may cause the model not to be found in rare cases, even though it is visible in the image. For GreedinessGreedinessGreedinessGreedinessgreedinessgreediness=1, the maximum search speed is achieved. In almost all cases, the deformable model will be found for GreedinessGreedinessGreedinessGreedinessgreedinessgreediness=0.9.

Output parameters in detail

HomMat2DHomMat2DHomMat2DHomMat2DhomMat2Dhom_mat_2d:

The projective transformation (homographies) that encode the position of the found instances of the model are returned in HomMat2DHomMat2DHomMat2DHomMat2DhomMat2Dhom_mat_2d. In case that multiple objects are found, the different homographies are concatenated. A single homography can easily be extracted by tuple_select_range(HomMat2D,Index*9,(Index+1)*9-1, SelectedHomMat2D)tuple_select_range(HomMat2D,Index*9,(Index+1)*9-1, SelectedHomMat2D)TupleSelectRange(HomMat2D,Index*9,(Index+1)*9-1, SelectedHomMat2D)TupleSelectRange(HomMat2D,Index*9,(Index+1)*9-1, SelectedHomMat2D)TupleSelectRange(HomMat2D,Index*9,(Index+1)*9-1, SelectedHomMat2D)tuple_select_range(HomMat2D,Index*9,(Index+1)*9-1, SelectedHomMat2D). The different detection results are sorted in decreasing order of ScoreScoreScoreScorescorescore. The row and column coordinates are the coordinates of the origin of the deformable model in the search image, which can be found by calling projective_trans_pixel(HomMat2D,0,0,Row,Column)projective_trans_pixel(HomMat2D,0,0,Row,Column)ProjectiveTransPixel(HomMat2D,0,0,Row,Column)ProjectiveTransPixel(HomMat2D,0,0,Row,Column)ProjectiveTransPixel(HomMat2D,0,0,Row,Column)projective_trans_pixel(HomMat2D,0,0,Row,Column). By default, the origin is the center of gravity of the domain (region) of the image that was used to create the deformable model with create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model. A different origin can be set with set_deformable_model_originset_deformable_model_originSetDeformableModelOriginSetDeformableModelOriginSetDeformableModelOriginset_deformable_model_origin. For visualization purposes, the model contours that are extracted by get_deformable_model_contoursget_deformable_model_contoursGetDeformableModelContoursGetDeformableModelContoursGetDeformableModelContoursget_deformable_model_contours can be projected to the found location given HomMat2DHomMat2DHomMat2DHomMat2DhomMat2Dhom_mat_2d with projective_trans_contour_xldprojective_trans_contour_xldProjectiveTransContourXldProjectiveTransContourXldProjectiveTransContourXldprojective_trans_contour_xld.

ScoreScoreScoreScorescorescore:

Additionally, the score of each found instance is returned in ScoreScoreScoreScorescorescore. The score is a number between 0 and 1, which is an approximate measure of how much of the model is visible in the image. If, for example, half of the model is occluded, the score cannot exceed 0.5.

Execution Information

• Multithreading type: reentrant (runs in parallel with non-exclusive operators).
• Multithreading scope: global (may be called from any thread).
• Automatically parallelized on internal data level.

Parameters

Result

If the parameters are valid, the operator find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model returns the value 2 (H_MSG_TRUE). If necessary an exception is raised.

Possible Predecessors

create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model, read_deformable_modelread_deformable_modelReadDeformableModelReadDeformableModelReadDeformableModelread_deformable_model

Alternatives

find_planar_calib_deformable_modelfind_planar_calib_deformable_modelFindPlanarCalibDeformableModelFindPlanarCalibDeformableModelFindPlanarCalibDeformableModelfind_planar_calib_deformable_model

Module

Matching