scholarly journals Human Face Pose Estimation based on Feature Extraction Points

2016 ◽  
Vol 142 (9) ◽  
pp. 41-43
Author(s):  
Guneet Bhullar ◽  
Vikram Mutneja
Keyword(s):  
Feature Extraction ◽  
Pose Estimation ◽  
Human Face

Hybrid Features Extraction for Adaptive Face Images Retrieval

2020 ◽  
Vol 11 (1) ◽  
pp. 17-26 ◽  
Author(s):  
Adel Alti
Keyword(s):  
Feature Extraction ◽  
Recognition Accuracy ◽  
Face Image ◽  
Human Face ◽  
Gradient Vector ◽  
Facial Image ◽  
Hybrid Features ◽  
Face Images ◽  
Hybrid Feature Extraction ◽  
Face Emotion Recognition

Existing methods of face emotion recognition have been limited in performance in terms of recognition accuracy and execution time. It is highly important to use efficient techniques for improving this performance. In this article, the authors present an automatic facial image retrieval combining the advantages of color normalization by texture estimators with the gradient vector. Starting from a query face image, an efficient algorithm for human face by hybrid feature extraction provides very interesting results.

Vehicle Pose Estimation and SONAR Sensor Based Mapping

2015 ◽  
Author(s):  
Hesham Ismail ◽  
Balakumar Balachandran
Keyword(s):  
Feature Extraction ◽  
Pose Estimation ◽  
Harsh Environments ◽  
Storage Tanks ◽  
Sonar Sensors ◽  
Oil Storage ◽  
Mobile Vehicle ◽  
Localization And Mapping ◽  
Sonar Sensor

In carrying out simultaneous localization and mapping, a mobile vehicle is used to simultaneously estimate its position and build a map of the environment. The long-term goal of this work is to build an autonomous inspection mobile vehicle for oil storage tanks and pipelines. The harsh environmental conditions in storage tanks and pipelines limit the types of feature extraction sensors and vehicle pose estimation sensors that one can use. Here, a SOund Navigation And Ranging (SONAR) sensor will be used for feature extraction, and a gyroscope and an encoder will be used for vehicle pose estimation. The integration of these sensors (SONAR, encoder, and gyroscope) will be discussed in this paper, along with the use of a recently developed algorithm fusion for SONAR sensors. The integration of the sensors represents a step towards implementation of concurrent localization and mapping progress in harsh environments.

Research of Face Identification Method Based on Geometric Feature Extraction and the Enlargement of Image Interpolation with Scientific Image Materials

2011 ◽  
Vol 63-64 ◽  
pp. 846-849
Author(s):  
Jian Ni ◽  
Yu Duo Li
Keyword(s):  
Feature Extraction ◽  
Feature Vector ◽  
Interpolation Method ◽  
Image Interpolation ◽  
Geometric Feature ◽  
Face Identification ◽  
Human Face ◽  
Training Experience ◽  
Geometric Feature Extraction ◽  
Vector Weight

To achieve human face identification, this paper adopts the method of geometric feature extraction and the enlargement of image interpolation on the basis of the completion of face detection. First of all, the input digital image will be normalized to reduce the complexity of the image, and then the feature of human face will be extract. With the feature information extracted, we can construct the feature vector and assign different weights to different feature vector. Weight is interpreted as the EXP obtained after a large amount of training experience is gained. Finally, to get the similarity of picture, the bilinear interpolation method is adopted on the basis of the nearest interpolation. Thus, we will get the results of face identification according to the similarity quality. Through the development and implementation of practical programming, this paper proves the feasibility of such method.

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