Detection Algorithm Research of Face Pose Based on Stereoscopic Vision and Biological Characteristics

2012 ◽  
Vol 460 ◽  
pp. 30-34
Author(s):  
Peng Xu ◽  
Yuan Men Zhou
Keyword(s):  
Face Recognition ◽  
Three Dimensional ◽  
Detection Algorithm ◽  
Stereoscopic Vision ◽  
Accuracy Rate ◽  
Face Images ◽  
Face Features ◽  
Key Points ◽  
Left And Right ◽  
The Impact

The paper introduces a kind of detection method of face pose based on stereoscopic vision technology, approximately divides head’s deflexion into three plane rotations. By calculating the deflexion angle of three directions, you can determine the face’s pose. This method obtains face images by the left and right video channels, first analyses the similarity of double channels’ images to obtain three-dimensional information of face features’ key points. Then calculates three deflexion angles according to these information, therefore can correspondingly adjust and deform the original image to get standard frontal face image, and provides correction image for the latter face recognition. By this method the impact of pose change to face recognition can be reduced obviously in the earlier stage, so the system’s overall recognition accuracy rate is enhanced effectively.

Human recognition from multi angular images

10.29007/cmts ◽  
2018 ◽  
Author(s):  
Rohan Naik ◽  
Kalpesh Lad
Keyword(s):  
Face Recognition ◽  
Detection Algorithm ◽  
Corner Detection ◽  
Human Face ◽  
Distance Method ◽  
Face Expression ◽  
Face Region ◽  
Face Images ◽  
Face Features ◽  
Harris Corner

Face recognition is still complicated task because to envision human actions might not realizable in each incident. Intention of face recognition is to identify human based on face that is similar from available dataset face images. Human face has multidimensional structure so it requires efficient technique for face harmonization and verification.Proposed work aim for developing efficient human face recognition method that deals with front as well as side view face in normal face expression. Using Viola–Jones face detection algorithm it accumulate only face region. Face features like eyes, nose and lip are extracted from whole face region using canny edge detection and harris corner detection method. To match individual face features, it compares position of edge boundary of features between images. Authors’ uses Euclidian distance method to retrieves maximum match value among all store face images. Based on threshold value it decides whether human face is recognized or not. Authors have evaluated performance of proposed method with DCT, DWD, PCA and LFL method on public free database like FEI, CVL and MIT-CBCL.

scholarly journals Kruskal-Wallis-Based Computationally Efficient Feature Selection for Face Recognition

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Sajid Ali Khan ◽  
Ayyaz Hussain ◽  
Abdul Basit ◽  
Sheeraz Akram
Keyword(s):  
Face Recognition ◽  
Recognition Accuracy ◽  
Facial Features ◽  
Face Database ◽  
Computationally Efficient ◽  
Accuracy Rate ◽  
Face Images ◽  
Face Features ◽  
Selection For ◽  
Technological World

Face recognition in today’s technological world, and face recognition applications attain much more importance. Most of the existing work used frontal face images to classify face image. However these techniques fail when applied on real world face images. The proposed technique effectively extracts the prominent facial features. Most of the features are redundant and do not contribute to representing face. In order to eliminate those redundant features, computationally efficient algorithm is used to select the more discriminative face features. Extracted features are then passed to classification step. In the classification step, different classifiers are ensemble to enhance the recognition accuracy rate as single classifier is unable to achieve the high accuracy. Experiments are performed on standard face database images and results are compared with existing techniques.

Research and Implementation of Face Detection Based on OpenCV

2014 ◽  
Vol 971-973 ◽  
pp. 1710-1713
Author(s):  
Wen Huan Wu ◽  
Ying Jun Zhao ◽  
Yong Fei Che
Keyword(s):  
Face Recognition ◽  
Detailed Analysis ◽  
Real Time ◽  
Face Detection ◽  
Recognition System ◽  
Detection Algorithm ◽  
High Accuracy ◽  
Accuracy Rate ◽  
Face Recognition System ◽  
The Face

Face detection is the key point in automatic face recognition system. This paper introduces the face detection algorithm with a cascade of Adaboost classifiers and how to configure OpenCV in MCVS. Using OpenCV realized the face detection. And a detailed analysis of the face detection results is presented. Through experiment, we found that the method used in this article has a high accuracy rate and better real-time.

scholarly journals Data Augmentation-Assisted Makeup-Invariant Face Recognition

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Muhammad Sajid ◽  
Nouman Ali ◽  
Saadat Hanif Dar ◽  
Naeem Iqbal Ratyal ◽  
Asif Raza Butt ◽  
...  
Keyword(s):  
Face Recognition ◽  
Data Augmentation ◽  
Recognition Performance ◽  
Recognition Task ◽  
Face Images ◽  
Face Features ◽  
Face Datasets ◽  
Exponential Rates ◽  
Interpersonal Situations

Recently, face datasets containing celebrities photos with facial makeup are growing at exponential rates, making their recognition very challenging. Existing face recognition methods rely on feature extraction and reference reranking to improve the performance. However face images with facial makeup carry inherent ambiguity due to artificial colors, shading, contouring, and varying skin tones, making recognition task more difficult. The problem becomes more confound as the makeup alters the bilateral size and symmetry of the certain face components such as eyes and lips affecting the distinctiveness of faces. The ambiguity becomes even worse when different days bring different facial makeup for celebrities owing to the context of interpersonal situations and current societal makeup trends. To cope with these artificial effects, we propose to use a deep convolutional neural network (dCNN) using augmented face dataset to extract discriminative features from face images containing synthetic makeup variations. The augmented dataset containing original face images and those with synthetic make up variations allows dCNN to learn face features in a variety of facial makeup. We also evaluate the role of partial and full makeup in face images to improve the recognition performance. The experimental results on two challenging face datasets show that the proposed approach can compete with the state of the art.

scholarly journals Simulation Technique of Kinematic Processes in the Vehicle Steering Linkage

2018 ◽  
Vol 7 (4.3) ◽  
pp. 120 ◽  
Author(s):  
Sergii Chernenko ◽  
Eduard Klimov ◽  
Andrii Chernish ◽  
Olexandr Pavlenko ◽  
Volodymyr Kukhar
Keyword(s):  
Three Dimensional ◽  
Simulation Technique ◽  
Design Parameters ◽  
Three Dimensional Model ◽  
Design Data ◽  
Power Characteristics ◽  
Left And Right ◽  
Turning Radius ◽  
The Impact ◽  
The Mathematical Model

The results of the investigation of the turning kinematics of the steerable wheels of the KrAZ-7634NE off-road vehicle with a wheel formula 8x8 and two front steer axles are given. The theoretical relations between the steer angles of the steerable wheels on the basis of the scheme of double-axle steering turning of the vehicle are shown. The mathematical model of flat four-bar vehicle steering linkage is developed, it determines the relation between the steering linkage left and right steering arms turning angles at any turning radius of the vehicle. KrAZ-7634HE steering three-dimensional model was created and simulation technique of its work was carried out using Creo software. It has been shown that the flat steering linkage model provides sufficient accuracy of calculations in analysis of turning kinematics. The design data can be used for any vehicles that have a similar steering linkage, they allow to analyze the impact of the vehicle design parameters on the turning kinematics and optimize them. Further study of the impact of the kingpin inclinations on the steering linkage kinematic and power characteristics are required.  

scholarly journals Template Based Pose and Illumination Invariant Face Recognition

2020 ◽  
Vol 8 (5) ◽  
pp. 3220-3229
Keyword(s):  
Face Recognition ◽  
Gabor Wavelet ◽  
Mathematical Methods ◽  
Query Image ◽  
Illumination Invariant ◽  
Face Images ◽  
The Face ◽  
Similar Images ◽  
Proper Face ◽  
The Impact

This article presents a method “Template based pose and illumination invariant face recognition”. We know that pose and Illumination are important variants where we cannot find proper face images for a given query image. As per the literature, previous methods are also not accurately calculating the pose and Illumination variants of a person face image. So we concentrated on pose and Illumination. Our System firstly calculates the face inclination or the pose of the head of a person with various mathematical methods. Then Our System removes the Illumination from the image using a Gabor phase based illumination invariant extraction strategy. In this strategy, the system normalizes changing light on face images, which can decrease the impact of fluctuating Illumination somewhat. Furthermore, a lot of 2D genuine Gabor wavelet with various orientations is utilized for image change, and numerous Gabor coefficients are consolidated into one entire in thinking about spectrum and phase. Finally, the light invariant is acquired by separating the phase feature from the consolidated coefficients. Then after that, the obtained Pose and illumination invariant images are convolved with Gabor filters to obtain Gabor images. Then templates will be extracted from these Gabor images and one template average is generated. Then similarity measure will be performed between query image template average and database images template averages. Finally the most similar images will be displayed to the user. Exploratory results on PubFig database, Yale B and CMU PIE face databases show that our technique got a critical improvement over other related strategies for face recognition under enormous pose and light variation conditions.

scholarly journals Three-Dimensional Biomechanical Finite Element Analysis of Lumbar Disc Herniation in Middle Aged and Elderly

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Shiyuan Wan ◽  
Bin Xue ◽  
Yanhao Xiong
Keyword(s):  
Finite Element ◽  
Intervertebral Disc ◽  
Lumbar Disc Herniation ◽  
Vertebral Body ◽  
Disc Herniation ◽  
Lumbar Disc ◽  
Three Dimensional ◽  
Surgical Methods ◽  
Left And Right ◽  
The Impact

Lumbar intervertebral disc protrusion disease refers to the degeneration of intervertebral disc, rupture of fibrous ring, nucleus pulpous protrusion and stimulation or compression of nerve root. The import command in Mimics medical 3D reconstruction software was used to erase the irrelevant image data and obtain vertebral body images. The original 3D model of each vertebral body was built by 3D computing function. A three-dimensional finite element model was established to analyze the effect of different surgical methods on the mechanical distribution of the spine after disentomb. The stress distribution of the spine, intervertebral disc, and left and right articular cartilage at L4/L5 stage and the position shift of the fourth lumbar vertebra were analyzed under 7 working conditions of vertical, forward flexion, extension, left and right flexion, and left and right rotation. The results showed that the established model was effective, and the smaller the area of posterior laminar decompression was, the lesser the impact on spinal stability was. The PELD treatment of lumbar disc herniation had little impact on spinal biomechanics and could achieve good long-term biomechanical stability. Combining the clinical experiment method and finite element simulation, using the advantages of finite element software to optimize the design function can provide guidance for the design and improvement of medical devices and has important significance for the study of clinical mechanical properties and biomechanics.

scholarly journals Three-dimensional face recognition using variance-based registration and subject-specific descriptors

2019 ◽  
Vol 16 (3) ◽  
pp. 172988141985171 ◽  
Author(s):  
Naeem Iqbal Ratyal ◽  
Imtiaz Ahmad Taj ◽  
Muhammad Sajid ◽  
Nouman Ali ◽  
Anzar Mahmood ◽  
...  
Keyword(s):  
Face Recognition ◽  
Three Dimensional ◽  
Recognition Algorithm ◽  
Superior Performance ◽  
Data Sets ◽  
Face Images ◽  
Subject Specific ◽  
The Face ◽  
The Subject ◽  
Depth Curves

Face recognition underpins numerous applications; however, the task is still challenging mainly due to the variability of facial pose appearance. The existing methods show competitive performance but they are still short of what is needed. This article presents an effective three-dimensional pose invariant face recognition approach based on subject-specific descriptors. This results in state-of-the-art performance and delivers competitive accuracies. In our method, the face images are registered by transforming their acquisition pose into frontal view using three-dimensional variance of the facial data. The face recognition algorithm is initialized by detecting iso-depth curves in a coordinate plane perpendicular to the subject gaze direction. In this plane, discriminating keypoints are detected on the iso-depth curves of the facial manifold to define subject-specific descriptors using subject-specific regions. Importantly, the proposed descriptors employ Kernel Fisher Analysis-based features leading to the face recognition process. The proposed approach classifies unseen faces by pooling performance figures obtained from underlying classification algorithms. On the challenging data sets, FRGC v2.0 and GavabDB, our method obtains face recognition accuracies of 99.8% and 100% yielding superior performance compared to the existing methods.

scholarly journals Neural architectures for stereo vision

2016 ◽  
Vol 371 (1697) ◽  
pp. 20150261 ◽  
Author(s):  
Andrew J. Parker ◽  
Jackson E. T. Smith ◽  
Kristine Krug
Keyword(s):  
Visual Cortex ◽  
Cortical Area ◽  
Binocular Disparity ◽  
Ocular Dominance ◽  
Three Dimensional ◽  
Stereoscopic Vision ◽  
Functional Modules ◽  
Repeat Distance ◽  
Left And Right ◽  
Cortical Architecture

Stereoscopic vision delivers a sense of depth based on binocular information but additionally acts as a mechanism for achieving correspondence between patterns arriving at the left and right eyes. We analyse quantitatively the cortical architecture for stereoscopic vision in two areas of macaque visual cortex. For primary visual cortex V1, the result is consistent with a module that is isotropic in cortical space with a diameter of at least 3 mm in surface extent. This implies that the module for stereo is larger than the repeat distance between ocular dominance columns in V1. By contrast, in the extrastriate cortical area V5/MT, which has a specialized architecture for stereo depth, the module for representation of stereo is about 1 mm in surface extent, so the representation of stereo in V5/MT is more compressed than V1 in terms of neural wiring of the neocortex. The surface extent estimated for stereo in V5/MT is consistent with measurements of its specialized domains for binocular disparity. Within V1, we suggest that long-range horizontal, anatomical connections form functional modules that serve both binocular and monocular pattern recognition: this common function may explain the distortion and disruption of monocular pattern vision observed in amblyopia. This article is part of the themed issue ‘Vision in our three-dimensional world’.

scholarly journals Can Plants Move like Animals? A Three-Dimensional Stereovision Analysis of Movement in Plants

Animals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1854
Author(s):  
Valentina Simonetti ◽  
Maria Bulgheroni ◽  
Silvia Guerra ◽  
Alessandro Peressotti ◽  
Francesca Peressotti ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Light Level ◽  
Stereoscopic Vision ◽  
Maximum Speed ◽  
Cycle Period ◽  
Movement Kinematics ◽  
Low Light ◽  
Automatic Tracking ◽  
Pisum Sativum L ◽  
Key Points

In this article we adapt a methodology customarily used to investigate movement in animals to study the movement of plants. The targeted movement is circumnutation, a helical organ movement widespread among plants. It is variable due to a different magnitude of the trajectory (amplitude) exhibited by the organ tip, duration of one cycle (period), circular, elliptical, pendulum-like or irregular shape and the clockwise and counterclockwise direction of rotation. The acquisition setup consists of two cameras used to obtain a stereoscopic vision for each plant. Cameras switch to infrared recording mode for low light level conditions, allowing continuous motion acquisition during the night. A dedicated software enables semi-automatic tracking of key points of the plant and reconstructs the 3D trajectory of each point along the whole movement. Three-dimensional trajectories for different points undergo a specific processing to compute those features suitable to describe circumnutation (e.g., maximum speed, circumnutation center, circumnutation length, etc.). By applying our method to the approach-to-grasp movement exhibited by climbing plants (Pisum sativum L.) it appears clear that the plants scale movement kinematics according to the features of the support in ways that are adaptive, flexible, anticipatory and goal-directed, reminiscent of how animals would act.

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