Titlebook: Computer Vision Systems; 10th International C Lazaros Nalpantidis,Volker Krüger,Antonios Gastera Conference proceedings 2015 Springer Inter

oracle

Quantitative Analysis of Surface Reconstruction Accuracy Achievable with the TSDF Representationic dataset of depth image sequences and corresponding camera pose ground truth and compare the reconstructed point clouds with the ground truth meshes. We investigate several influencing factors, especially the TSDF resolution and show that the TSDF is a very powerful representation even for low resolutions.

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arrogant

oncologist

Learning Appearance Features for Pain Detection Using the UNBC-McMaster Shoulder Pain Expression Arcing appearance features that separate pain-related factors from other factors, such as those related to the identity of the face. The system achieves state-of-the-art performance on the UNBC-McMaster Shoulder Pain Expression Archive Database.

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0302-9743 rdware-implemented and real-time vision systems; high-level vision; learning and adaptation; robot vision; and vision systems applications.978-3-319-20903-6978-3-319-20904-3Series ISSN 0302-9743 Series E-ISSN 1611-3349

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https://doi.org/10.1007/978-3-662-03725-6een the queried signature and all the data set signatures. To address the scalability problem of using shape context for signature matching, the proposed method speeds up the matching stage by representing the shape context features as a feature vector and then applies a clustering algorithm to assign signatures to their corresponding classes.

Defense

An Overview of Numbers in Computersobtained using metric learning in the base of Structural SVM Ranking. It improves the discriminative and accuracy performance of re-identification. Compared with the similar algorithms, the method achieves higher re-identification rate with more comprehensive similarity measure.

IDEAS

Linear and Logistic Regression,ing appearance features that separate pain-related factors from other factors, such as those related to the identity of the face. The system achieves state-of-the-art performance on the UNBC-McMaster Shoulder Pain Expression Archive Database.