Head Pose Estimation Using Multi-scale Gaussian Derivatives
نویسندگان
چکیده
In this paper we approach the problem of head pose estimation by combining Multi-scale Gaussian Derivatives with Support Vector Machines. We evaluate the approach on the Pointing04 and CMU-PIE data sets and to estimate the pan and tilt of the head from facial images. We achieved a mean absolute error of 6.9 degrees for pan and 8.0 degrees for tilt on the Pointing04 data set.
منابع مشابه
Head Pose Estimation in Seminar Room Using Multi View Face Detectors
Head pose estimation in low resolution is a challenge problem. Traditional pose estimation algorithms, which assume faces have been well aligned before pose estimation, would face much difficulty in this situation, since face alignment itself does not work well in this low resolution scenario. In this paper, we propose to estimate head pose using viewbased multi-view face detectors directly. Na...
متن کاملMulti-level structured hybrid forest for joint head detection and pose estimation
In real-world applications, factors such as illumination variation, occlusion, and poor image quality, etc. make head detection and pose estimation much more challenging. In this paper, we propose a multi-level structured hybrid forest (MSHF) for joint head detection and pose estimation. Our method extends the hybrid framework of classification and regression forests by introducing multi-level ...
متن کاملMachine Observation of the Direction of Human Visual Focus of Attention
People often look at objects and people with which they are likely to interact. The first step for computer systems to adapt to the user and to improve interaction and with people is to locate where they are, and especially the location of their faces on the image. The next step is to track their focus of attention. For this reason, we are interested in techniques for estimating and tracking ga...
متن کاملTowards Multilevel Human Body Modeling and Tracking in 3D: Investigation in Laplacian Eigenspace (LE) Based Initialization and Kinematically Constrained Gaussian Mixture Modeling (KC-GMM)
Vision-based automatic human body pose estimation has many potential applications and it is also a challenging task. Together, these two factors have made vision-based human body pose estimation an attractive research area with closely related research areas including body pose, hand pose, and head pose estimation. Up to now, these research works however only deal with each task of estimating b...
متن کاملDynamical Pose Filtering for Mixtures of Gaussian Processes
In this paper we present a method for performing discriminative human pose estimation using a mixture of Gaussian Processes appearance model to map directly from the image features to the multi-model pose distribution. In order to obtain a pose estimate for a sequence of frames, we introduce a dynamic programming algorithm for inferring a smooth pose sequence from the multi-model distribution g...
متن کامل