We propose an efficient method for object localization and 3D pose estimation. A two-step approach is used. In the first step, a pose estimator is evaluated in the input images in order to estimate potential object locations and poses. These candidates are then validated, in the second step, by the corresponding pose-specific classifier. The result is a detection approach that avoids the inhere...

Pose Estimation With Low-Resolution Bearing-Only Sensors

Human perception shows that a correct interpretation of a 3D scene on the basis of a 2D image is possible without markers. Solely by identifying natural features of different objects, their locations and orientations on the image can be identified. This allows a three dimensional interpretation of a two dimensional pictured scene. The key aspect for this interpretation is the correct estimation...

Accurate markerless motion capture systems rely on images that allow segmentation of the person in the foreground. While the accuracy of such approaches is comparable to marker based systems, the segmentation step makes strong restrictions to the capture environment, e.g. homogenous clothing or background, constant lighting etc. In our approach a template model is fitted to images by an Analysi...

In this paper, a new pose estimation solution for perspective vision system is presented and applied to a civil aircraft landing phase. Vision sensor is used to overcome the need of external technologies and runway knowledge. First-of-all, an existing structure of observation is applied to real landing scenarios; in this case, an observability analysis highlights some limitations of this soluti...

In order to perform coherent and robust interpretation of moving faces, one must resolve the inconsistency and ambiguities observed among multiple sources of highly noisy visual measurements. In this work, we describe a method for perceptual fusion through the estimation of observation covariance. We demonstrate the approach through a working system that performs real-time face detection and tr...

In this paper, we propose a method to estimate 3D shape of deformable plastic tapes from multiple camera images. In this method, the tape is modeled as serial connection of multiple rectangular plates, where the size of each plate is previously known and node angles of between plates represent the shape of the object. The node angles of the object are estimated by 2D silhouette shapes taken in ...

Estimating the pose of a rigid body means to determine the rigid body motion in the 3D space from 2D images. For this purpose, it is reasonable to make use of existing knowledge of the object. Our approach exploits the 3D shape and the texture of the tracked object in form of a 3D textured model to establish 3D2D correspondences for pose estimation. While the surface of the 3D free-form model i...

We present an algorithm to estimate the 3D pose (location and orientation) of a previously unseen face from low-quality range images. The algorithm generates many pose candidates from a signature to find the nose tip based on local shape, and then evaluates each candidate by computing an error function. Our algorithm incorporates 2D and 3D cues to make the system robust to low-quality range ima...

Pedestrian misalignment, which mainly arises from detector errors and pose variations, is a critical problem for a robust person re-identification (re-ID) system. With bad alignment, the background noise will significantly compromise the feature learning and and matching process. To address this problem, this paper introduces the pose invariant embedding (PIE) as a pedestrian descriptor. First,...