Tracking and Learning Graphs and Pose on Image Sequences of Faces
نویسندگان
چکیده
We demonstrate a system capable of tracking, in real world image sequences, landmarks such as eyes, mouth, or chin on a face. In the standard version, knowledge previously collected about faces is used for finding the landmarks in the first frame. In a second version, the system is able to track the face without any prior knowledge about faces and is thus applicable to other object classes. By using Gabor filters as visual features, and by both avoiding limiting assumptions and many parameters our tracking tool is simple and easy to use. As a first application the tracking results are used to estimate the pose of a face.
منابع مشابه
Tracking and Learning Graphs on Image Sequences of Faces
We demonstrate a system capable of tracking, in real world image sequences, landmarks such as eyes, mouth, or chin on a face. In a rst version knowledge previously collected about faces is used for nding the landmarks in the rst frame. In a second version the system is able to track the face without any prior knowledge about faces and is thus applicable to other object classes.
متن کاملNeural Network Performance Analysis for Real Time Hand Gesture Tracking Based on Hu Moment and Hybrid Features
This paper presents a comparison study between the multilayer perceptron (MLP) and radial basis function (RBF) neural networks with supervised learning and back propagation algorithm to track hand gestures. Both networks have two output classes which are hand and face. Skin is detected by a regional based algorithm in the image, and then networks are applied on video sequences frame by frame in...
متن کاملLearning to Identify and Track Faces in Image Sequences
We address the problem of robust face identification in the presence of pose, lighting, and expression variation. Previous approaches to the problem have assumed similar models of variation for each individual, estimated from pooled training data. We describe a method of updating a first order global estimate of identity by learning the class-specific correlation between the estimate and the re...
متن کاملLearning a Warped Subspace Model of Faces with Images of Unknown Pose and Illumination
In this paper we tackle the problem of learning the appearances of a person’s face from images with both unknown pose and illumination. The unknown, simultaneous change in pose and illumination makes it difficult to learn 3D face models from data without manual labeling and tracking of features. In comparison, image-based models do not require geometric knowledge of faces but only the statistic...
متن کاملUsing a Novel Concept of Potential Pixel Energy for Object Tracking
Abstract In this paper, we propose a new method for kernel based object tracking which tracks the complete non rigid object. Definition the union image blob and mapping it to a new representation which we named as potential pixels matrix are the main part of tracking algorithm. The union image blob is constructed by expanding the previous object region based on the histogram feature. The pote...
متن کامل