To avoid high dimensional facial shape regression, we propose a hierarchical pose regression approach, estimating the head rotation, face components, and facial landmarks hierarchically.
Moving Pose [41] proposes a moving pose descriptor for capturing dynamic postures, by using the configuration, speed, and acceleration of the skeleton joints.
We use 3D human pose data as additional information and propose a compact human pose representation, called a weak pose, in a low-dimensional space while still keeping the most discriminative information for a given pose.
This paper proposes a new pose estimation algorithm in the framework of robotic navigation problems.
This paper proposes a robust pose classification framework based on dictionary-learning and sparse representation.
In this paper, we have proposed a head pose estimation approach using a single camera in order to identify driver inattention.
For example, Murphy-Chutorian and Trivedi [6] proposed a head pose detection systems for monitoring driver awareness application using Haar-wavelet AdabooSVMclassifiersVM clandifiers, appearance-basedased 3D particle filter (PF) tracking.
In this paper we propose a fast 3D pose based SLAM system that estimates a vehicle's trajectory by registering sets of planar surface segments, extracted from 360∘ field of view (FOV) point clouds provided by a 3D LIDAR.
We propose a novel pose-invariant face recognition approach which we call Discriminant Multiple Coupled Latent Subspace framework.
Motivated by these studies and the potential of AV-ASR in human-computer interfaces [12], we propose to introduce a pose normalization step in a system designed for frontal views, i.e., we generate virtual frontal views from the non-frontal images and rely on the existing frontal visual models to recognize speech.
