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Spatial Gabor energy filters (GE) are one of the most successful approaches to represent facial expressions in computer vision applications, including face recognition and expression analysis. It is well known that these filters approximate the response of complex cells in primary visual cortex. However these neurons are modulated by the temporal, not just spatial, properties of the visual signal...
This paper presents the first investigation into the classification of faces from unconstrained video sequences in natural scenes, i.e., with arbitrary poses, facial expressions, occlusions, illumination conditions and motion blur. To overcome difficulties from individual frames, a novel Bayesian formulation is proposed to estimate the posterior probability of a face trait at a specific time, conditional...
We recognize actions and activities in video sequences as distinguishing patterns in the 3D spatiotemporal volume of motion energy. Local motion descriptors, which capture highly discriminative invariant motion characteristics in a spherical neighborhood, are computed in the 3D volume at points of salient motion to represent actions or activities in video sequences. Two actions are then matched based...
In this work, we address the recognition of human activities from a sequence of visual data. To this end, a novel hierarchical probabilistic latent (HPL) model is proposed, which consists of four layers from bottom-up: spatiotemporal visual features layer, atomic pattern layer, latent topic layer, and behavior pattern layer. In this manner, the complicated human activities can be decomposed into low...
We introduce a unified framework for scene structure and motion estimation on road-driving stereo sequences. This framework is based on the slanted-plane scene model that has become widely popular in the stereo vision community. Our algorithm iteratively and alternately solves for scene structure and motion. Surface estimation is done using our own slanted-plane stereo algorithm. Motion estimation...
This paper presents an automatic 3D head pose initialization scheme for a real-time face tracker with application to human-robot interaction. It has two main contributions. First, we propose an automatic 3D head pose and person specific face shape estimation, based on a 3D deformable model. The proposed approach serves to initialize our real-time 3D face tracker. What makes this contribution very...
In this paper, we present a system for indoor human localization that does not need 3D reconstruction of features or landmarks. We assume that a video sequence has been acquired and that keyframes have been registered with respect to 2D positions and orientations. In online mode, we use only a handheld monochrome fisheye camera and a synchronized IMU as sensory inputs. The query is not based on a...
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