Articulated motion and deformable objects : 10th International Conference, AMDO 2018, Palma de Mallorca, Spain, July 12-13, 2018, Proceedings

Responsibility
edited by Francisco José Perales, Josef Kittler.
Digital
text file; PDF
Publication
Cham : Springer, 2018.
Physical description
1 online resource (x, 131 pages)
Series
Lecture notes in computer science ; 10945. 0302-9743
LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics.

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Description

Contents/Summary

Contents
  • Intro
  • Preface
  • Organization
  • Contents
  • Mammographic Mass Segmentation Using Fuzzy C-means and Decision Trees
  • 1 Introduction
  • 2 Segmentation of Masses in Mammograms Using Fuzzy C-means and Decision Trees
  • 2.1 Fuzzy C-means Based on Gray Levels Histogram
  • 2.2 Reduction of False Positive ROIs
  • 2.3 Feature Extraction
  • 2.4 Binary Decision Tree
  • 3 Experimentation
  • 3.1 Results and Discussion
  • 4 Conclusions
  • References
  • Refining the Pose: Training and Use of Deep Recurrent Autoencoders for Improving Human Pose Estimation
  • 1 Introduction
  • 2 Deep Architecture for 3D Human Pose Refinement
  • 2.1 Denoising Recurrent Autoencoder
  • 2.2 Convolutional Network for Pose Prediction
  • 2.3 Pose Refinement Training
  • 2.4 Cost Function
  • 3 Experiments
  • 3.1 Evaluation on HumanEva-I
  • 3.2 Evaluation on Human 3.6 Million
  • 3.3 Ablation Experiments
  • 3.4 Conclusions
  • References
  • How Can Deep Neural Networks Be Generated Efficiently for Devices with Limited Resources?
  • 1 Introduction
  • 2 Background
  • 3 Parameter Pruning
  • 4 Quantization
  • 5 Low-Rank Factorization
  • 6 Compact Network Design
  • 7 Neural Model Deployment
  • 7.1 Compact Network Design
  • 7.2 Training and Pruning
  • 7.3 Quantize Model
  • 7.4 Inference Optimization
  • 8 Conclusion
  • References
  • Controlling a Smartphone with Brain-Computer Interfaces: A Preliminary Study
  • 1 Introduction
  • 2 Subjects and Methods
  • 2.1 Acquisition
  • 2.2 Processing
  • 2.3 Application
  • 2.4 Evaluation Procedure
  • 3 Results
  • 4 Discussion
  • 5 Conclusion
  • References
  • Capturing Industrial Machinery into Virtual Reality
  • 1 Introduction
  • 2 Related Work
  • 3 System Design
  • 3.1 Initialisation
  • 3.2 Capturing Images
  • 3.3 Calibration
  • 3.4 Visualisation
  • 4 Results
  • 5 Conclusion
  • References
  • Leishmaniasis Parasite Segmentation and Classification Using Deep Learning
  • 1 Introduction
  • 2 Data
  • 3 Method
  • 4 Results
  • 5 Conclusions
  • References
  • Robust Pedestrian Detection for Semi-automatic Construction of a Crowded Person Re-Identification Dataset
  • 1 Introduction
  • 2 The JNU Dataset
  • 3 Automatic Pedestrian Detection
  • 4 Automatic Data Association
  • 5 Evaluation
  • 6 Conclusion
  • References
  • Shape and Appearance Based Sequenced Convnets to Detect Real-Time Face Attributes on Mobile Devices
  • 1 Introduction
  • 2 Related Work
  • 3 Datasets and Data Preparation
  • 3.1 FER-2013 and FER+ Datasets
  • 3.2 Data Preprocessing
  • 4 Proposed CNN Architecture
  • 4.1 Sequenced CNN Models
  • 4.2 Face Heatmap Image Construction
  • 4.3 CNN Models
  • 4.4 Learning with a Shape Heatmap Image
  • 5 Results and Applications
  • 5.1 Effects of Data Preparation and Alignment
  • 5.2 Combining Face Shape and Appearance with VGG
  • 5.3 Combining Face Shape and Appearance with Mobilenet
  • 5.4 Implementation
  • 6 Conclusions
  • References
  • Image Colorization Using Generative Adversarial Networks
  • 1 Introduction
Publisher's summary
This book constitutes the refereed proceedings of the 10th International Conference on Articulated Motion and Deformable Objects, AMDO 2018, held in Palma de Mallorca, Spain, in July 2018. The 12 papers presented were carefully reviewed and selected from 26 submissions. The papers address the following topics: advanced computer graphics and immersive videogames; human modeling and animation; human motion analysis and tracking; 3D human reconstruction and recognition; multimodal user interaction and applications; ubiquitous and social computing; design tools; input technology; programming user interfaces; 3D medical deformable models and visualization; deep learning methods for computer vision and graphics; and multibiometric.
(source: Nielsen Book Data)

Bibliographic information

Publication date
2018
Title variation
AMDO 2018
Series
Lecture Notes in Computer Science, 0302-9743 ; 10945
LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics
ISBN
9783319945446
3319945440
9783319945439
3319945432
DOI
10.1007/978-3-319-94544-6

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