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Empirical evaluation methods in computer vision [[electronic resource] /] / editors, Henrik I. Christensen, P. Jonathon Phillips
| Empirical evaluation methods in computer vision [[electronic resource] /] / editors, Henrik I. Christensen, P. Jonathon Phillips |
| Pubbl/distr/stampa | River Edge, N.J., : World Scientific, c2002 |
| Descrizione fisica | 1 online resource (172 p.) |
| Disciplina | 006.3/7 |
| Altri autori (Persone) |
ChristensenH. I <1962-> (Henrik I.)
PhillipsP. Jonathon |
| Collana | Series in machine perception and artificial intelligence |
| Soggetto topico | Computer vision - Evaluation |
| Soggetto genere / forma | Electronic books. |
| ISBN | 981-277-742-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents ; Foreword ; Chapter 1 Automated Performance Evaluation of Range Image Segmentation Algorithms ; 1.1. Introduction ; 1.2. Scoring the Segmented Regions ; 1.3. Segmentation Performance Curves ; 1.4. Training of Algorithm Parameters ; 1.5. Train-and-Test Performance Evaluation
1.6. Training Stage 1.7. Testing Stage ; 1.8. Summary and Discussion ; References ; Chapter 2 Training/Test Data Partitioning for Empirical Performance Evaluation ; 2.1. Introduction ; 2.2. Formal Problem Definition ; 2.2.1. Distance Function ; 2.2.2. Computational Complexity 2.3. Genetic Search Algorithm 2.4. A Testbed ; 2.5. Experimental Results ; 2.6. Conclusions ; References ; Chapter 3 Analyzing PCA-based Face Recognition Algorithms: Eigenvector Selection and Distance Measures ; 3.1. Introduction ; 3.2. The FERET Database ; 3.3. Distance Measures 3.3.1. Adding Distance Measures 3.3.2. Distance Measure Aggregation ; 3.3.3. Correlating Distance Metrics ; 3.3.4. When Is a Difference Significant ; 3.4. Selecting Eigenvectors ; 3.4.1. Removing the Last Eigenvectors ; 3.4.2. Removing the First Eigenvector 3.4.3. Eigenvalue Ordered by Like-Image Difference 3.4.4. Variation Associated with Different Test/Training Sets ; 3.5. Conclusion ; References ; Chapter 4 Design of a Visual System for Detecting Natural Events by the Use of an Independent Visual Estimate: A Human Fall Detector 4.1. Introduction |
| Record Nr. | UNINA-9910458199803321 |
| River Edge, N.J., : World Scientific, c2002 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Empirical evaluation methods in computer vision [[electronic resource] /] / editors, Henrik I. Christensen, P. Jonathon Phillips
| Empirical evaluation methods in computer vision [[electronic resource] /] / editors, Henrik I. Christensen, P. Jonathon Phillips |
| Pubbl/distr/stampa | River Edge, N.J., : World Scientific, c2002 |
| Descrizione fisica | 1 online resource (172 p.) |
| Disciplina | 006.3/7 |
| Altri autori (Persone) |
ChristensenH. I <1962-> (Henrik I.)
PhillipsP. Jonathon |
| Collana | Series in machine perception and artificial intelligence |
| Soggetto topico | Computer vision - Evaluation |
| ISBN | 981-277-742-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents ; Foreword ; Chapter 1 Automated Performance Evaluation of Range Image Segmentation Algorithms ; 1.1. Introduction ; 1.2. Scoring the Segmented Regions ; 1.3. Segmentation Performance Curves ; 1.4. Training of Algorithm Parameters ; 1.5. Train-and-Test Performance Evaluation
1.6. Training Stage 1.7. Testing Stage ; 1.8. Summary and Discussion ; References ; Chapter 2 Training/Test Data Partitioning for Empirical Performance Evaluation ; 2.1. Introduction ; 2.2. Formal Problem Definition ; 2.2.1. Distance Function ; 2.2.2. Computational Complexity 2.3. Genetic Search Algorithm 2.4. A Testbed ; 2.5. Experimental Results ; 2.6. Conclusions ; References ; Chapter 3 Analyzing PCA-based Face Recognition Algorithms: Eigenvector Selection and Distance Measures ; 3.1. Introduction ; 3.2. The FERET Database ; 3.3. Distance Measures 3.3.1. Adding Distance Measures 3.3.2. Distance Measure Aggregation ; 3.3.3. Correlating Distance Metrics ; 3.3.4. When Is a Difference Significant ; 3.4. Selecting Eigenvectors ; 3.4.1. Removing the Last Eigenvectors ; 3.4.2. Removing the First Eigenvector 3.4.3. Eigenvalue Ordered by Like-Image Difference 3.4.4. Variation Associated with Different Test/Training Sets ; 3.5. Conclusion ; References ; Chapter 4 Design of a Visual System for Detecting Natural Events by the Use of an Independent Visual Estimate: A Human Fall Detector 4.1. Introduction |
| Record Nr. | UNINA-9910784783003321 |
| River Edge, N.J., : World Scientific, c2002 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Empirical evaluation methods in computer vision [[electronic resource] /] / editors, Henrik I. Christensen, P. Jonathon Phillips
| Empirical evaluation methods in computer vision [[electronic resource] /] / editors, Henrik I. Christensen, P. Jonathon Phillips |
| Pubbl/distr/stampa | River Edge, N.J., : World Scientific, c2002 |
| Descrizione fisica | 1 online resource (172 p.) |
| Disciplina | 006.3/7 |
| Altri autori (Persone) |
ChristensenH. I <1962-> (Henrik I.)
PhillipsP. Jonathon |
| Collana | Series in machine perception and artificial intelligence |
| Soggetto topico | Computer vision - Evaluation |
| ISBN | 981-277-742-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents ; Foreword ; Chapter 1 Automated Performance Evaluation of Range Image Segmentation Algorithms ; 1.1. Introduction ; 1.2. Scoring the Segmented Regions ; 1.3. Segmentation Performance Curves ; 1.4. Training of Algorithm Parameters ; 1.5. Train-and-Test Performance Evaluation
1.6. Training Stage 1.7. Testing Stage ; 1.8. Summary and Discussion ; References ; Chapter 2 Training/Test Data Partitioning for Empirical Performance Evaluation ; 2.1. Introduction ; 2.2. Formal Problem Definition ; 2.2.1. Distance Function ; 2.2.2. Computational Complexity 2.3. Genetic Search Algorithm 2.4. A Testbed ; 2.5. Experimental Results ; 2.6. Conclusions ; References ; Chapter 3 Analyzing PCA-based Face Recognition Algorithms: Eigenvector Selection and Distance Measures ; 3.1. Introduction ; 3.2. The FERET Database ; 3.3. Distance Measures 3.3.1. Adding Distance Measures 3.3.2. Distance Measure Aggregation ; 3.3.3. Correlating Distance Metrics ; 3.3.4. When Is a Difference Significant ; 3.4. Selecting Eigenvectors ; 3.4.1. Removing the Last Eigenvectors ; 3.4.2. Removing the First Eigenvector 3.4.3. Eigenvalue Ordered by Like-Image Difference 3.4.4. Variation Associated with Different Test/Training Sets ; 3.5. Conclusion ; References ; Chapter 4 Design of a Visual System for Detecting Natural Events by the Use of an Independent Visual Estimate: A Human Fall Detector 4.1. Introduction |
| Record Nr. | UNINA-9910810146703321 |
| River Edge, N.J., : World Scientific, c2002 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
