Object Recognition By Affine Invariant Matching
Object Recognition By Affine Invariant Matching
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Finally, we have done experiments to test our convex curve matching algo- rithm. Fig. 10 displays two models of convex objects and Fig. 12 gives their recog- nition results. We took artificial objects made of cardboard, since we had difficulty finding non polygonal 'real' convex objects. We especially chose objects with a 'smooth' boundary curve so that no special anchor points on the boundary could be identified. Fig. 16a shows another (significantly tilted) image of the model in Fig. 10a, and... Fig. 16b displays its recognition and the basis region and triplet where it was achieved. This basis region was selected in the footprint correspondence pro- cedure described in Section 6. 2.
Figure 16 : a) Tilted image of the object in Fig. 10a. B) Recognition result with corresponding basis region.
Fig. 17 shows another overlapping scene of the convex models of Fig. 10, and their recognition.
23 Figure 17 : a) Tilted composite scene of the objects in Fig. 10. B) Recognition.
9. Conclusions and Future Research In this paper we present methods for object recognition under the assumption of affine approximation to the perspective transformation.
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To quickly assess the difficulty of the text, read a short excerpt:
Finally, we have done experiments to test our convex curve matching algo- rithm. Fig. 10 displays two models of convex objects and Fig. 12 gives their recog- nition results. We took artificial objects made of cardboard, since we had difficulty finding non polygonal 'real' convex objects. We especially chose objects with a 'smooth' boundary curve so that no special anchor points on the boundary could be identified. Fig. 16a shows another (significantly tilted) image of the model in Fig. 10a, and... Fig. 16b displays its recognition and the basis region and triplet where it was achieved. This basis region was selected in the footprint correspondence pro- cedure described in Section 6. 2.
Figure 16 : a) Tilted image of the object in Fig. 10a. B) Recognition result with corresponding basis region.
Fig. 17 shows another overlapping scene of the convex models of Fig. 10, and their recognition.
23 Figure 17 : a) Tilted composite scene of the objects in Fig. 10. B) Recognition.
9. Conclusions and Future Research In this paper we present methods for object recognition under the assumption of affine approximation to the perspective transformation.
What to read after Object Recognition By Affine Invariant Matching?
You can find similar books in the "Read Also" column, or choose other free books by Yehezkel Lamdan to read onlineMoreLess
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