create_planar_uncalib_deformable_modelT_create_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model (Operator)

Name

create_planar_uncalib_deformable_modelT_create_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model — Creates a deformable model for uncalibrated, perspective matching.

Signature

Description

The operator create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model prepares a template, which is passed in the image TemplateTemplateTemplateTemplatetemplatetemplate, as a deformable model used for uncalibrated perspective matching. The ROI of the model is passed as the domain of TemplateTemplateTemplateTemplatetemplatetemplate.

The planar uncalibrated matching can be used to detect planar objects or planar subparts of non-planar objects that are distorted by a projective view.

This is an alternative to create_generic_shape_modelcreate_generic_shape_modelCreateGenericShapeModelCreateGenericShapeModelCreateGenericShapeModelcreate_generic_shape_model, where typically the search image must be rectified by calibrate_camerascalibrate_camerasCalibrateCamerasCalibrateCamerasCalibrateCamerascalibrate_cameras and gen_image_to_world_plane_mapgen_image_to_world_plane_mapGenImageToWorldPlaneMapGenImageToWorldPlaneMapGenImageToWorldPlaneMapgen_image_to_world_plane_map beforehand.

In contrast to create_shape_model_3dcreate_shape_model_3dCreateShapeModel3dCreateShapeModel3dCreateShapeModel3dcreate_shape_model_3d there is no need to pre-generate different views of an object, resulting into a smaller memory consumption. Hence, in case of a planar perspectively distorted object, create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model should be preferred.

The model is generated using multiple image pyramid levels and is stored in memory. The output parameter ModelIDModelIDModelIDModelIDmodelIDmodel_id is a handle for this model, which is used in subsequent calls to find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model.

Input parameters in detail

NumLevelsNumLevelsNumLevelsNumLevelsnumLevelsnum_levels:

The number of pyramid levels is determined with the parameter NumLevelsNumLevelsNumLevelsNumLevelsnumLevelsnum_levels. It should be chosen as large as possible because by this the time necessary to find the object is significantly reduced. On the other hand, NumLevelsNumLevelsNumLevelsNumLevelsnumLevelsnum_levels must be chosen such that the model is still recognizable and contains a sufficient number of points on the highest pyramid level. If not enough model points are generated, the number of pyramid levels is reduced internally until enough model points are found on the highest pyramid level. If this procedure would lead to a model with no pyramid levels, i.e., if the number of model points is already too small on the lowest pyramid level, create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model returns with an error message. If NumLevelsNumLevelsNumLevelsNumLevelsnumLevelsnum_levels is set to 'auto'"auto""auto""auto""auto""auto", create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model determines the number of pyramid levels automatically. The automatically computed number of pyramid levels can be queried using get_deformable_model_paramsget_deformable_model_paramsGetDeformableModelParamsGetDeformableModelParamsGetDeformableModelParamsget_deformable_model_params. In rare cases, it might happen that create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model determines a value for the number of pyramid levels that is too large or too small. If the number of pyramid levels is chosen too large, the model may not be recognized in the image or it may be necessary to select very low parameters for MinScoreMinScoreMinScoreMinScoreminScoremin_score or GreedinessGreedinessGreedinessGreedinessgreedinessgreediness in find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model in order to find the model. If the number of pyramid levels is chosen too small, the time required to find the model in find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model increases. In these cases, the number of pyramid levels should be selected using the output of inspect_shape_modelinspect_shape_modelInspectShapeModelInspectShapeModelInspectShapeModelinspect_shape_model.

Angle and Scale parameters:

Note that the parameters AngleStartAngleStartAngleStartAngleStartangleStartangle_start, AngleExtentAngleExtentAngleExtentAngleExtentangleExtentangle_extent, ScaleRMaxScaleRMaxScaleRMaxScaleRMaxscaleRMaxscale_rmax, and ScaleCMaxScaleCMaxScaleCMaxScaleCMaxscaleCMaxscale_cmax are not used by this operator. Instead, they have to be specified within the operator find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model. ScaleRMinScaleRMinScaleRMinScaleRMinscaleRMinscale_rmin and ScaleCMinScaleCMinScaleCMinScaleCMinscaleCMinscale_cmin can be relevant if you expect matches that are smaller than in the original image TemplateTemplateTemplateTemplatetemplatetemplate. Then, if NumLevelsNumLevelsNumLevelsNumLevelsnumLevelsnum_levels is set to 'auto'"auto""auto""auto""auto""auto", the number of used pyramid levels may decrease.

Generally, the parameters AngleStepAngleStepAngleStepAngleStepangleStepangle_step, ScaleRStepScaleRStepScaleRStepScaleRStepscaleRStepscale_rstep and ScaleCStepScaleCStepScaleCStepScaleCStepscaleCStepscale_cstep can be determined automatically. The automatically computed angle and scale step lengths can be queried using get_deformable_model_paramsget_deformable_model_paramsGetDeformableModelParamsGetDeformableModelParamsGetDeformableModelParamsget_deformable_model_params. For more information about how these parameters work, please refer to the operator find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model.

OptimizationOptimizationOptimizationOptimizationoptimizationoptimization:

For particularly large models, it may be useful to reduce the number of model points by setting OptimizationOptimizationOptimizationOptimizationoptimizationoptimization to a value different from 'none'"none""none""none""none""none". If OptimizationOptimizationOptimizationOptimizationoptimizationoptimization = 'none'"none""none""none""none""none", all model points are stored. In all other cases, the number of points is reduced according to the value of OptimizationOptimizationOptimizationOptimizationoptimizationoptimization. If the number of points is reduced, it may be necessary in find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model to set the parameter ScoreScoreScoreScorescorescore and GreedinessGreedinessGreedinessGreedinessgreedinessgreediness to a smaller value as, e.g., 0.7 or 0.8. For small models, the reduction of the number of model points does not result in a speed-up of the search because in this case usually significantly more potential instances of the model must be examined. If OptimizationOptimizationOptimizationOptimizationoptimizationoptimization is set to 'auto'"auto""auto""auto""auto""auto", create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model automatically determines the reduction of the number of model points.

ContrastContrastContrastContrastcontrastcontrast:

The parameter ContrastContrastContrastContrastcontrastcontrast determines the contrast the model points (edges) must have. The contrast is a measure for local gray value differences between the object and the background and between different parts of the object. ContrastContrastContrastContrastcontrastcontrast should be chosen such that only the significant features of the template are used for the model.

The following values can be set for ContrastContrastContrastContrastcontrastcontrast:

• A single contrast value. You can set:

  • an integer value: the manually determined value is used.

  • 'auto_contrast'"auto_contrast""auto_contrast""auto_contrast""auto_contrast""auto_contrast": the contrast value is computed automatically.

• Hysteresis thresholds. In this case, the model is segmented using a method similar to the hysteresis threshold method used in edges_imageedges_imageEdgesImageEdgesImageEdgesImageedges_image. For more information about the hysteresis threshold method, see hysteresis_thresholdhysteresis_thresholdHysteresisThresholdHysteresisThresholdHysteresisThresholdhysteresis_threshold. You can set:

  • A tuple of two values: The first value determines the lower threshold, the second value determines the upper threshold.

  • 'auto'"auto""auto""auto""auto""auto" (default value) or 'auto_contrast_hyst'"auto_contrast_hyst""auto_contrast_hyst""auto_contrast_hyst""auto_contrast_hyst""auto_contrast_hyst": The hysteresis thresholds are computed automatically.

In certain cases, it might happen that the automatic determination of the contrast thresholds is not satisfying. For example, a manual setting of these parameters should be preferred if certain model components should be included or suppressed because of application-specific reasons or if the object contains several different contrasts. Therefore, the contrast thresholds should be automatically determined with determine_deformable_model_paramsdetermine_deformable_model_paramsDetermineDeformableModelParamsDetermineDeformableModelParamsDetermineDeformableModelParamsdetermine_deformable_model_params and subsequently verified using inspect_shape_modelinspect_shape_modelInspectShapeModelInspectShapeModelInspectShapeModelinspect_shape_model before calling create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model. Note that MinContrastMinContrastMinContrastMinContrastminContrastmin_contrast influences the automatic contrast estimation, and hence also the estimation of the minimum size.

MinContrastMinContrastMinContrastMinContrastminContrastmin_contrast:

With MinContrastMinContrastMinContrastMinContrastminContrastmin_contrast, it can be determined which minimal contrast the model must have in the recognition performed by find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model. In other words, this parameter separates the model from the noise in the image. Therefore, a good choice is the range of gray value changes caused by the noise in the image. If, for example, the gray values fluctuate within a range of 10 gray levels, MinContrastMinContrastMinContrastMinContrastminContrastmin_contrast should be set to 10. Obviously, MinContrastMinContrastMinContrastMinContrastminContrastmin_contrast must be smaller than ContrastContrastContrastContrastcontrastcontrast. If the model should be recognized in very low contrast images, MinContrastMinContrastMinContrastMinContrastminContrastmin_contrast must be set to a correspondingly small value. If the model should be recognized even if it is severely occluded, MinContrastMinContrastMinContrastMinContrastminContrastmin_contrast should be slightly larger than the range of gray value fluctuations created by noise in order to ensure that the position and rotation of the model are extracted robustly and accurately by find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model. If MinContrastMinContrastMinContrastMinContrastminContrastmin_contrast is set to 'auto'"auto""auto""auto""auto""auto", the minimum contrast is determined automatically based on the noise in the model image. Consequently, an automatic determination only makes sense if the image noise during the recognition is similar to the noise in the model image. Furthermore, in some cases it is advisable to increase the automatically determined value in order to increase the robustness against occlusions (see above). The automatically computed minimum contrast can be queried using get_deformable_model_paramsget_deformable_model_paramsGetDeformableModelParamsGetDeformableModelParamsGetDeformableModelParamsget_deformable_model_params. The MinContrastMinContrastMinContrastMinContrastminContrastmin_contrast of a deformable model can later be changed with the help of set_deformable_model_paramset_deformable_model_paramSetDeformableModelParamSetDeformableModelParamSetDeformableModelParamset_deformable_model_param.

MetricMetricMetricMetricmetricmetric:

The parameter MetricMetricMetricMetricmetricmetric determines the conditions under which the model is recognized in the image. If MetricMetricMetricMetricmetricmetric = 'use_polarity'"use_polarity""use_polarity""use_polarity""use_polarity""use_polarity", the object in the image and the model must have the same contrast. If, for example, the model is a bright object on a dark background, the object is found only if it is also brighter than the background. If MetricMetricMetricMetricmetricmetric = 'ignore_global_polarity'"ignore_global_polarity""ignore_global_polarity""ignore_global_polarity""ignore_global_polarity""ignore_global_polarity", the object is found in the image also if the contrast reverses globally. In the above example, the object hence is also found if it is darker than the background. The runtime of find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model will increase slightly in this case. If MetricMetricMetricMetricmetricmetric = 'ignore_part_polarity'"ignore_part_polarity""ignore_part_polarity""ignore_part_polarity""ignore_part_polarity""ignore_part_polarity", the the contrast polarity is allowed to change only between different parts of the model, whereas the polarity of model points that are within the same model part must not change. Please note that the term 'ignore_part_polarity'"ignore_part_polarity""ignore_part_polarity""ignore_part_polarity""ignore_part_polarity""ignore_part_polarity" is capable of being misunderstood. It means that polarity changes between neighboring model parts do not influence the score, and hence are ignored. If MetricMetricMetricMetricmetricmetric = 'ignore_local_polarity'"ignore_local_polarity""ignore_local_polarity""ignore_local_polarity""ignore_local_polarity""ignore_local_polarity", the model is found even if the contrast changes for each individual model point. This mode can, for example, be useful if the object consists of a part with medium gray value, within which either darker or brighter sub-objects lie. In this case the runtime of find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model increases significantly. The above four metrics can only be applied to single-channel images. If a multichannel image is used as the model image or as the search image only the first channel will be used (and no error message will be returned). If MetricMetricMetricMetricmetricmetric = 'ignore_color_polarity'"ignore_color_polarity""ignore_color_polarity""ignore_color_polarity""ignore_color_polarity""ignore_color_polarity", the model is found even if the color contrast changes locally. This is, for example, the case if parts of the object can change their color, e.g., from red to green. In particular, this mode is useful if it is not known in advance in which channels the object is visible. In this mode, the runtime of find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model can also increase significantly. The metric 'ignore_color_polarity'"ignore_color_polarity""ignore_color_polarity""ignore_color_polarity""ignore_color_polarity""ignore_color_polarity" can be used for images with an arbitrary number of channels. If it is used for single-channel images it has the same effect as 'ignore_local_polarity'"ignore_local_polarity""ignore_local_polarity""ignore_local_polarity""ignore_local_polarity""ignore_local_polarity". It should be noted that for MetricMetricMetricMetricmetricmetric = 'ignore_color_polarity'"ignore_color_polarity""ignore_color_polarity""ignore_color_polarity""ignore_color_polarity""ignore_color_polarity" the number of channels in the model creation with create_planar_uncalib_deformable_modelcreate_planar_uncalib_deformable_modelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelCreatePlanarUncalibDeformableModelcreate_planar_uncalib_deformable_model and in the search with find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model can be different. This can, for example, be used to create a model from a synthetically generated single-channel image. Furthermore, it should be noted that the channels do not need to contain a spectral subdivision of the light (like in an RGB image). The channels can, for example, also contain images of the same object that were obtained by illuminating the object from different directions.

GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name, GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value:

With the help of the generic parameters GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name and GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value, the user can set parameters for the deformable model generation that are needed only in rare cases. Currently, it is used to adapt the average size of the sub-parts that the deformable model should consist of. Here, GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name should be set to 'part_size'"part_size""part_size""part_size""part_size""part_size" and GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value should be set to 'small'"small""small""small""small""small", 'medium'"medium""medium""medium""medium""medium" or 'big'"big""big""big""big""big". For objects that consist of many small contours, 'small'"small""small""small""small""small" should be selected. For objects that consist of only big contours, 'big'"big""big""big""big""big" should be set. The default value of this parameter is 'big'"big""big""big""big""big".

Optionally, GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name = 'min_size'"min_size""min_size""min_size""min_size""min_size" can determine a threshold for the selection of significant model components based on the size of the components, i.e., components that have fewer points than the minimum size specified in the corresponding GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value are suppressed. This threshold for the minimum size is divided by two for each successive pyramid level. 'min_size'"min_size""min_size""min_size""min_size""min_size" can be set to an arbitrary integer value greater or equal 0. It can also be set to 'auto'"auto""auto""auto""auto""auto" which means that the minimum size will be determined automatically. The default value of this parameter is 'auto'"auto""auto""auto""auto""auto".

The center of gravity of the domain (region) of the model image TemplateTemplateTemplateTemplatetemplatetemplate is used as the origin (reference point) of the model. A different origin for the model can be set with set_deformable_model_originset_deformable_model_originSetDeformableModelOriginSetDeformableModelOriginSetDeformableModelOriginset_deformable_model_origin.

Execution Information

• Multithreading type: reentrant (runs in parallel with non-exclusive operators).
• Multithreading scope: global (may be called from any thread).
• Processed without parallelization.

This operator returns a handle. Note that the state of an instance of this handle type may be changed by specific operators even though the handle is used as an input parameter by those operators.

Parameters

Result

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

Possible Predecessors

determine_deformable_model_paramsdetermine_deformable_model_paramsDetermineDeformableModelParamsDetermineDeformableModelParamsDetermineDeformableModelParamsdetermine_deformable_model_params

Possible Successors

set_deformable_model_originset_deformable_model_originSetDeformableModelOriginSetDeformableModelOriginSetDeformableModelOriginset_deformable_model_origin, set_deformable_model_paramset_deformable_model_paramSetDeformableModelParamSetDeformableModelParamSetDeformableModelParamset_deformable_model_param, get_deformable_model_contoursget_deformable_model_contoursGetDeformableModelContoursGetDeformableModelContoursGetDeformableModelContoursget_deformable_model_contours, find_planar_uncalib_deformable_modelfind_planar_uncalib_deformable_modelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelFindPlanarUncalibDeformableModelfind_planar_uncalib_deformable_model, get_deformable_model_paramsget_deformable_model_paramsGetDeformableModelParamsGetDeformableModelParamsGetDeformableModelParamsget_deformable_model_params, write_deformable_modelwrite_deformable_modelWriteDeformableModelWriteDeformableModelWriteDeformableModelwrite_deformable_model, clear_deformable_modelclear_deformable_modelClearDeformableModelClearDeformableModelClearDeformableModelclear_deformable_model

Alternatives

read_deformable_modelread_deformable_modelReadDeformableModelReadDeformableModelReadDeformableModelread_deformable_model

Module

Matching