Wolfgang Sepp

Recurrent V1–V2 interaction in early visual boundary processing

Abstract. A majority of cortical areas are connected via feedforward and feedback fiber projections. In feedforward pathways we mainly observe stages of feature detection and integration. The computational role of the descending pathways at different stages of processing remains mainly unknown. Based on empirical findings we suggest that the top-down feedback pathways subserve a context-dependent gain control mechanism. We propose a new computational model for recurrent contour processing in which normalized activities of orientation selective contrast cells are fed forward to the next processing stage. There, the arrangement of input activation is matched against local patterns of contour shape. The resulting activities are subsequently fed back to the previous stage to locally enhance those initial measurements that are consistent with the top-down generated responses. In all, we suggest a computational theory for recurrent processing in the visual cortex in which the significance of local measurements is evaluated on the basis of a broader visual context that is represented in terms of contour code patterns. The model serves as a framework to link physiological with perceptual data gathered in psychophysical experiments. It handles a variety of perceptual phenomena, such as the local grouping of fragmented shape outline, texture surround and density effects, and the interpolation of illusory contours.

Tracking local motion on the beating heart

Local motion on the beating heart is investigated in the context of minimally invasive robotic surgery. The focus lies on the motion remaining in the mechanically stabilised field of surgery of the heart. Motion is detected by tracking natural landmarks on the heart surface in 2D video images. An appropriate motion model is presented with a discussion of its degrees of freedom and a trajectory analysis of its parameters.

The DLR multisensory Hand-Guided Device: the Laser Stripe Profiler

This paper presents the DLR Laser Stripe Profiler as a component of the DLR multisensory Hand-Guided Device for 3D modeling. After modeling the reconstruction process, we propose a novel method for laser plane self-calibration based on the assessment of the deformations the miscalibration leads to. In addition, the requirement for absence of optical filtering implies the development of a robust stripe segmentation algorithm. Experiments demonstrate the validity and applicability of the approaches.

Reconstruction of Image Structure in Presence of Specular Reflections

This paper deals with the reconstruction of original image structure in the presence of local disturbances such as specular reflections. It presents two novel schemes for their elimination with respect to the local image structure: an efficient linear interpolation scheme and an iterative filling-in approach employing anisotropic diffusion. The algorithms are evaluated on images of the heart surface and are suited to support tracking of natural landmarks on the beating heart.

The self-referenced DLR 3D-modeler

In the context of 3-D scene modeling, this work aims at the accurate estimation of the pose of a close-range 3-D modeling device, in real-time and passively from its own images. This novel development makes it possible to abandon using inconvenient, expensive external positioning systems. The approach comprises an ego-motion algorithm tracking natural, distinctive features, concurrently with customary 3-D modeling of the scene. The use of stereo vision, an inertial measurement unit, and robust cost functions for pose estimation further increases performance. Demonstrations and abundant video material validate the approach.

Using a model of the reachable workspace to position mobile manipulators for 3-d trajectories

Humanoid robots are envisioned in general household tasks. To be able to fulfill a given task the robot needs to be equipped with knowledge concerning the manipulation and interaction in the environment and with knowledge about its own capabilities. When performing actions, e.g. opening doors or imitating human reach to grasp movements special 3-d trajectories are followed with the robots end-effector. These trajectories can not be executed in every part of the robots arm workspace. Therefore a task planner has to determine if and how additional degrees of freedom such as the robots upper body or the robots base can be moved in order to execute the task-specific trajectory. An approach is presented that computes placements for a mobile manipulator online given a task-related 3-d trajectory. A discrete representation of the robot arms reachable workspace is used. Task-specific trajectories are interpreted as patterns and searched in the reachability model using multi-dimensional correlation. The relevance of the presented approach is demonstrated in simulated positioning tasks.

Hierarchical Featureless Tracking for Position-Based 6-DoF Visual Servoing

Classical position-based visual servoing approaches rely on the presence of distinctive features in the image such as corners and edges. In this contribution we exploit a hierarchical approach for object detection, initial-pose estimation, and real-time tracking based first on colour distribution and subsequently on the shape and texture information. The shape model of the object is not limited to surface primitives but allow for any free-form surface not subject to self-occlusion. We evaluate the approach as part of a handshake scenario where a 7-DoF robot takes a free moving object over from a human

Recurrent long-range interactions in early vision

A general principle of cortical architecture is the bidirectional flow of information along feedforward and feedback connections. In the feedforward path, converging connections mainly define the feature detection characteristics of cells. The computational role of feedback connections, on the contrary, is largely unknown. Based on empirical findings we suggest that top-down feedback projections modulate activity of target cells in a context dependent manner. The context is represented by the spatial extension and direction of long-range connections. In this scheme, bottom-up activity which is consistent in a more global context is enhanced, inconsistent activity is suppressed. We present two instantiations of this general scheme having complementary functionality, namely a model of cortico-cortical V1-V2 interactions and a model of recurrent intracortical V1 interactions. The models both have long-range interactions for the representation of contour shapes and modulating feedback in common. They differ in their response properties to illusory contours and corners, and in the details of computing the bipole filter which models the long-range connections. We demonstrate that the models are capable of basic processing tasks in vision, such as, e.g., contour enhancement, noise suppression and corner detection. Also, a variety of perceptual phenomena such as grouping of fragmented shape outline and interpolation of illusory contours can be explained.

On the issue of camera calibration with narrow angular field of view

This paper considers the issue of calibrating a camera with narrow angular field of view using standard, perspective methods in computer vision. In doing so, the significance of perspective distortion both for camera calibration and for pose estimation is revealed. Since narrow angular field of view cameras make it difficult to obtain rich images in terms of perspectivity, the accuracy of the calibration results is expectedly low. From this, we propose an alternative method that compensates for this loss by utilizing the pose readings of a robotic manipulator. It facilitates accurate pose estimation by nonlinear optimization, minimizing reprojection errors and errors in the manipulator transformations at the same time. Accurate pose estimation in turn enables accurate parametrization of a perspective camera.

Real-Time Texture-Based 3-D Tracking

We present a tracking approach for textured surfaces which recovers the object motion in 6 degrees of freedom. We assume an arbitrary but known surface shape, and an image of the object at a known reference pose. We extend the 2-D tracking framework of Hager et al. [1] to tracking in 3-D and under full perspective projection. The algorithm is evaluated to ground-truth motion and shows high accuracy. Thanks to problem-specific optimizations we achive tracking at video-rate.