Showing papers by "Avinash C. Kak published in 2005"

Person Tracking with a Mobile Robot using Two Uncalibrated Independently Moving Cameras

Abstract: This paper presents an efficient person tracking algorithm for a vision-based mobile robot using two independently moving cameras each of which is mounted on its own pan/tilt unit. Without calibrating these cameras, the goal of our proposed method is to estimate the distance to a target appearing in the image sequences captured by the cameras. The main contributions of our approach include: 1) establishing the correspondence between the control inputs to the pan/tilt units and the pixel displacement in the image plane without using the intrinsic parameters of the cameras; and 2) derivation of the distance information from the correspondence between the centers of masses of the segmented color-blobs from the left and the right images without stereo camera calibration. Our proposed approach has been successfully tested on a mobile robot for the task of person following in real environments.

A New Approach to the Use of Edge Extremities for Model-based Object Tracking

Abstract: This paper presents a robust model-based visual tracking algorithm that can give accurate 3D pose of a rigid object. Our tracking algorithm uses an incremental pose update scheme in a prediction-verification framework. Extended Kalman filter is used to update the pose of a target incrementally to minimize the error between the expected map of the target model and the corresponding gradient edge in the image space. The main contributions of this paper include: 1) A novel approach to how we use the two extremities of straight-lines as features. By taking into account the measurement uncertainties associated with the locations of the extracted extremities of the straight-line, our approach can compare correctly two straight-lines of different lengths. 2) Our use of a test of mean criterion for initiating backtracking and our use of a variable threshold on the output of this criterion that makes nil-matching more effective. We have tested our tracking algorithm with image sequences containing highly cluttered backgrounds. The system successfully tracks objects even when they are highly occluded.

Accurate 3D Tracking of Rigid Objects with Occlusion Using Active Appearance Models

Abstract: In this paper we present a new method for tracking rigid objects using a modified version of the Active Appearance Model. Unlike most of the other appearance-based methods in the literature, our method allows for both partial and self occlusion of the objects. We use ground-truth to demonstrate the accuracy of our tracking algorithm. We show that our method can be applied to track moving objects over wide variations in position and orientation of the object - one meter in translation and 140 degrees in rotation - with an accuracy of a few millimeters.

Metrics for analyzing module interactions in large software systems

Abstract: We present a new set of metrics for analyzing the interaction between the modules of a large software system. We believe that these metrics would be important to any automatic or semi-automatic code modularization algorithm. The metrics are based on the rationale that code partitioning should be based on the principle of similarity of service provided by the different functions encapsulated in a module. Although module interaction metrics are necessary for code modularization, in practice they must be accompanied by metrics that measure other important attributes of how the code is partitioned into modules. These other metrics, dealing with code properties such as the approximate uniformity of module sizes, conformance to any size constraints on the modules, etc., are also included in the work presented here. To give the reader some insight into the workings of our metrics, this paper also includes some results obtained by applying the metrics to the body of code that constitutes the open-source Apache HTTP server. We apply our metrics to this code as packaged by the developers of the software and to the other partially and fully randomized versions of the code.