Figure 1 - available via license: Creative Commons Attribution 3.0 Unported
Content may be subject to copyright.
The final scheme of face detection algorithm using CEDT approach
Source publication
Face detection algorithm based on a cascade of ensembles of decision trees (CEDT) is presented. The new approach allows detecting faces other than the front position through the use of multiple classifiers. Each classifier is trained for a specific range of angles of the rotation head. The results showed a high rate of productivity for CEDT on imag...
Similar publications
This paper aims to develop a machine learning and deep learning-based real-time framework for detecting and recognizing human faces in closed-circuit television (CCTV) images. The traditional CCTV system needs a human for 24/7 monitoring, which is costly and insufficient. The automatic recognition system of faces in CCTV images with minimum human i...
Citations
... In the last years, face detection has gained greater attention in fields of biometrics [20], pattern recognition [21] and computer vision [22]. Despite this operation is already implemented in almost every device of everyday life, face detection requires better performance in terms of robustness, especially for biometrics or medical applications. ...
Three-dimensional data has a wide range of applications in medicine. For the particular case of cranial deformation in infants, it is becoming a common tool for evaluation. However, there is a need for low-cost solutions that provide accurate information even with uncollaborative infants with ultrafast movement reactions. As cranial deformation is often linked to facial abnormalities, facial information is required for comprehensive evaluation.
In this study, the integration of target-based close-range photogrammetry and facial landmark machine learning detection is carried out. The resulting tool is automatic and smartphone-based and provides 3D information of the head and face. This methodology opens a new path for the effective integration of machine learning and photogrammetry in medicine and, in particular, for overall head analysis.
... Second, the research focuses on the study of public sports culture practice teaching content, such as [4][5][6] "Sports Practice Teaching Content System Research" that proposed the horizontal "sport cycle" theory of sports textbooks and vertically divides sports based on the characteristics of students' physical and mental development. A new system of physical education teaching content is established [7][8][9]. Third, the research involves interdisciplinary research, such as psychological research methods for the study of public physical education in colleges in the "Selection and Personality Relationship of College Students' Physical Education Option Courses" [10]. The field of teaching evaluation integrates actual public sports culture. ...
... (4) If the attribute_ list is empty, proceed to (5); (5) Return N as a leaf node and mark it as the category with the largest number of categories in the sample contained in the node; (6) Select an attribute test_ attribute with the largest information gain from the attribute_list; (7) Mark node N as test_attribute; (8) For each known value a i in the test_ attribute, prepare a sample set included in the partition node N; (9) According to the test_ attribute=a i condition, a corresponding branch is generated from the node N to indicate the test condition; (10) Let S i be the sample set obtained by the test_ attribute=ai condition; (11) If S i is empty, mark the corresponding leaf node as the category with the largest number of categories in the sample contained in the node; (12) Otherwise, mark the corresponding leaf node as the Generate_Decision_Tree return value. and the prediction model is generated. ...
The public sports culture of colleges is based on the basic skills and strategies of the public sports culture curriculum. The study of public sports culture in colleges focuses on the unity and standardization of teaching forms, structures, contents, methods, assessments, and evaluations. This paper considers the various links that affect the public sports culture of colleges, identifies frequent item sets, and gains support by establishing support and confidence thresholds. The frequent item sets of the degrees and confidence with the rules generated by a decision tree algorithm are compared to identify the key factors that affect the actual effect. This paper fully considers the public sports culture of colleges to comprehensively analyze the relevant factors, verify and compare the rules generated by the decision tree algorithm, and identify the key factors that affect the actual effect. By an example verification, the method of this paper has certain guiding value for the study of public sports culture.
... The Viola-Jones algorithm is a classical face detection method that uses signs based on Haar wavelet features, which are black and white rectangles. It generates the sum of pixel intensities in many rectangles in an image based on threshold values [24,25]. If no face is detected in this phase, the algorithm continues to the second phase; otherwise, it jumps to the third phase. ...
This paper presents a novel technique for Face Recognition from a Partial Face View (FRPV), which consists of three phases. The first phase uses an existing algorithm to detect faces in input images. The second phase includes splitting the input images undetected by the first phase into two, four, six, or eight parts. Then, every part is rotated by a new split and rotate face detection (SRFD) algorithm until it detects a face in one of these partial images. The third phase uses the Eigenfaces method with train and test databases to perform recognition. This phase compares the selected test image with images in the train database until it recognizes the person and updates the train database. The FRPV system was implemented using a head-pose image database where every person has multiple images with several poses having different Pitch and Yaw Angles ranging from –90º to +90º. The results showed that the FRPV system outperformed previous methods. Its accuracy rate was equal to 96% for faces that had different poses. In addition, the SRFD method achieved a detection success rate of 67%, which is better than other similar methods.
