In this paper, an efficient algorithm for human face detection and facial feature extraction is devised. Firstly, the location of the face regions is detected using the genetic algorithm and the eigenface techn
Due to some limitation of neural network based methods we adopt the Adaboost algorithm for face detection. Here we present Some results on real world examples are presented. Our detector found good detection rates with frontal faces and the method can be easily adapted to other object detection ...
In this example, you created a simple face tracking system that automatically detects and tracks a single face. Try changing the input video, and see if you are still able to detect and track a face. Make sure the person is facing the camera in the initial frame for the detection step...
Fortunately, the programming model and abstractions are very similar among the various APIs. This means you should be able to map the concepts learned in OpenCL to other APIs without difficulty. Let’s now dive into an OpenCL implementation for face detection....
Fortunately, the programming model and abstractions are very similar among the various APIs. This means you should be able to map the concepts learned in OpenCL to other APIs without difficulty. Let’s now dive into an OpenCL implementation for face detection....
For face recognition, an adaptively weighted patch of pseudo-Zernike moments has been used [31]. Different OMs have been used in this field, such as higher-order OMs [32], Fourier–Mellin moments [33], rotation-invariant complex Zernike moments [34], discrete Krawtchouk moments [35], ...
A face detection algorithm. Contribute to Sierkinhane/mtcnn-pytorch development by creating an account on GitHub.
The proposed algorithm is robust to negative effects such as dust, light, shadows, and occlusions, and is well-suited for masked-face detection in industrial and public scenarios. The proposed model is tested on the VOC dataset and the AIZOO open-source masked-face dataset, obtaining 5.58% AP...
Modern systems rely on rapid analysis of large or continuous datasets, whether for fraud detection, sensor monitoring, or customer recommendations. Toptal data engineers design algorithms that process high-volume or streaming data with consistent accuracy and speed, even as input loads grow. Optimizati...
$ git clone https://github.com/sthanhng/yoloface For face detection, you should download the pre-trained YOLOv3 weights file which trained on the WIDER FACE: A Face Detection Benchmark dataset from this link and place it in the model-weights/ directory. Run the following command: image ...