Author name cluster

Michael Boshra

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

3 papers

1 author row

ICRA Conference 1996 Conference Paper

An efficient pixel-based technique for visual verification of 3-D object hypotheses

Michael Boshra
Hong Zhang 0013

The technique proceeds in three steps: firstly, the visible-edge image of the hypothesized model object is constructed; secondly, this image is superimposed on the scene edge image; finally, corresponding pixels in the two images are compared to gather votes for the validity of the hypothesis. Uncertainty in estimating the locations of both scene and model edge pixels is handled by dilating the scene edge image. An analytical method is presented for determining the extent of dilation, assuming some error bound on the object pose. The proposed technique has several important advantages over the common feature-based techniques. Firstly, it is much simpler to implement. Secondly, the time complexity of verifying a hypothesis is made independent of the scene complexity (number and types of scene features). Thirdly, it is insensitive to imperfections of the feature extraction process. Finally the technique is easy to implement on the existing parallel vision/graphics hardware; thus it is suitable for real-time applications.

Details

IROS Conference 1995 Conference Paper

A constraint-satisfaction approach for 3D vision/touch-based object recognition

Michael Boshra
Hong Zhang 0013

We present a technique for recognizing polyhedral objects by integrating visual and tactile data. The problem is formulated as a constraint-satisfaction problem (CSP) to provide a unified framework for integrating different types of sensory data. To make use of the scene perceptual structures early in the recognition process, we enforce local consistency of the CSP. The process of local-consistency enforcing (LCE) reduces the correspondence uncertainty between scene and model features, which can lead to significant reductions in the computational load on subsequent recognition modules. LCE can also eliminate many erroneous model objects efficiently, without explicitly generating or verifying any object/pose hypotheses.

Details

IROS Conference 1994 Conference Paper

Use of visual and tactile data for generation of 3-D object hypotheses

Michael Boshra
Hong Zhang 0013

Most existing 3-D object recognition/localization systems rely on a single type of sensory data, although several sensors may be available in a robot task to provide information about the objects to be recognized. In this paper, the authors present a technique to localize polyhedral objects by integrating visual and tactile data. It is assumed that visual data is provided by a monocular visual sensor, while tactile data by a planar-array tactile sensor in contact with the object to be localized. The authors focus on using tactile data in the hypothesis generation phase to reduce the requirements of visual features for localization to a V-junction only. The main concept of this technique is to compute a set of partial pose hypotheses off-line by utilizing tactile data, and then complement these partial hypotheses on-line using visual data. The technique presented is tested using simulated and real data. >

Details