Contents III. 1 Introduction 1

Transcription

1 III Contents 1 Introduction 1 2 The Parametric Distributional Clustering Model The Data Acquisition Process The Generative Model The Likelihood Function A different view on the PDC cost function Model Identification E-Step Equations M-Step Equations Multi-Scale Techniques Experimental Results Implementation Details Test-Set and Evaluation Methodology Color Segmentation Combined Color and Texture Segmentation Summary Bibliographic Remarks Incorporating Topological Constraints Spatial Topology The Cost Function for Spatially Coupled PDC Model Identification for spdc Experimental Evaluation Topology in Cluster-Space The Segmentation Model TPDC Model Identification: Experimental Results Combining Spatial and Group Topology The stpdc Model stpdc Model Identification Experimental Evaluation Summary Bibliographic Remarks:

2 IV Contents 4 Robustness and Generalization Bootstrap Resampling The Resampling Strategy Evaluation Results Generalizing Segmentation Solutions The Generalization Problem Experimental Setup and Results Summary Bibliographic Remarks Shape Constrained Segmentation Introduction Representing Shape Knowledge Aspect Sets Combining Shape and Segmentation Implementation and Experimental Results Dataset and Features Shape Prior Construction Aspect Model Generation Prior Alignment Shape Constrained Image Segmentation Generalization To Other Semantic Categories Summary Bibliographic Remarks Conclusion 113 A Box-Plots for recall, precision, and F-measure distributions 117

3 V 2.1 The real-part of an example Gabor-function Illustration of the data acquisition process Graphical model of the image formation process Effects of the number of data groups on color-only PDC image segmentations Comparison between segmentation results of the human subjects and color-only PDC (first collection) Comparison between segmentation results of the human subjects and color-only PDC (second collection) Effects of the number of data groups on PDC image segmentations according to color and texture cues Comparison between human and PDC segmentations based on color and texture Result comparison of color-only PDC and PDC using color and texture features Examples of spdc vs. PDC image partitions Comparison of spdc segmentation results and human image partitions Empirical CDFs of performance measure differences between spdc and PDC Topological coupling between neighboring clusters TPDC segmentation result on artificial test-data TPDC with chain topology applied to real-world data TPDC segmentation results with five clusters stpdc segmentations compared to human image partitions (result collection 1) stpdc segmentations compared to human image partitions (result collection 2) Empirical CDFs of performance measure differences between stpdc and TPDC Visualization of the bootstrap sampling process Second stage of resampling process for image data

4 VI 4.3 Joint recall-precision-curve for the discussed resampling examples Human segmentation compared to aggregated bootstrap edges for image Human segmentation compared to aggregated bootstrap edges for image Human segmentation compared to aggregated bootstrap edges for image Human segmentation compared to aggregated bootstrap edges for image Human segmentation compared to aggregated bootstrap edges for image Human segmentation compared to aggregated bootstrap edges for image Human segmentation compared to aggregated bootstrap edges for image Generalizing spdc solutions, example image pair one Generalizing spdc solutions, example image pair two Generalizing spdc solutions, example image pair three Generalizing spdc solutions, example image pair four Generalizing spdc solutions, example image pair five Generalizing spdc solutions, example image pair six Generalizing spdc solutions, example image pair seven Prior shape model construction Graphical model of the SCS approach SCS processing pipeline Sketchy hand-segmentations in shape prior construction Symbolic depiction of the geometry in PDC cost-space Aspect likelihoods in comparison to PDC costs Results of the scaled prior alignment procedure Shape constrained segmentation results, (example set one) Shape constrained segmentation results (example set two) Comparison between segmentations with and without shape constraints (example set one) Shape constrained segmentation results (example set three) Comparison between segmentations with and without shape constraints (example set two) A.1 Recall, precision and F-measure distributions for color-only PDC with three clusters A.2 Recall, precision and F-measure distributions for color-only PDC with five clusters

5 VII A.3 Recall, precision and F-measure distributions for color-only PDC with eight clusters A.4 Recall, precision and F-measure distributions for PDC with three clusters using color and texture features A.5 Recall, precision and F-measure distributions for PDC with five clusters using color and texture features A.6 Recall, precision and F-measure distributions for PDC with eight clusters using color and texture features A.7 Recall, precision and F-measure distributions for spdc with three clusters using color and texture features A.8 Recall, precision and F-measure distributions for spdc with five clusters using color and texture features A.9 Recall, precision and F-measure distributions for spdc with eight clusters using color and texture features A.10 Recall, precision and F-measure distributions for TPDC with three clusters using color and texture features A.11 Recall, precision and F-measure distributions for TPDC with five clusters using color and texture features A.12 Recall, precision and F-measure distributions for TPDC with eight clusters using color and texture features A.13 Recall, precision and F-measure distributions for stpdc with three clusters using color and texture features A.14 Recall, precision and F-measure distributions for stpdc with five clusters using color and texture features A.15 Recall, precision and F-measure distributions for stpdc with eight clusters using color and texture features

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7 IX List of Tables 2.1 Recall, Precision and F-value summary for color-only PDC Recall, Precision and F-value summary for combined color & texture PDC Recall, Precision and F-value summary for spdc Recall, Precision and F-value summary for TPDC Recall, Precision and F-value summary for stpdc Resampling evaluation summary for image Resampling evaluation summary for image Resampling evaluation summary for image Resampling evaluation summary for image Resampling evaluation summary for image Resampling evaluation summary for image Resampling evaluation summary for image