Method for targetless tracking subpixel in-plane movements

We present a targetless motion tracking method for detecting planar movements with subpixel accuracy. This method is based on the computation and tracking of the intersection of two nonparallel straight-line segments in the image of a moving object in a scene. The method is simple and easy to implement because no complex structures have to be detected. It has been tested and validated using a lab experiment consisting of a vibrating object that was recorded with a high-speed camera working at 1000 fps. We managed to track displacements with an accuracy of hundredths of pixel or even of thousandths of pixel in the case of tracking harmonic vibrations. The method is widely applicable because it can be used for distance measuring amplitude and frequency of vibrations with a vision system.

On the suitability of Prototype Selection methods for kNN classification with distributed data

In the current Information Age, data production and processing demands are ever increasing. This has motivated the appearance of large-scale distributed information. This phenomenon also applies to Pattern Recognition so that classic and common algorithms, such as the k-Nearest Neighbour, are unable to be used. To improve the efficiency of this classifier, Prototype Selection (PS) strategies can be used. Nevertheless, current PS algorithms were not designed to deal with distributed data, and their performance is therefore unknown under these conditions. This work is devoted to carrying out an experimental study on a simulated framework in which PS strategies can be compared under classical conditions as well as those expected in distributed scenarios. Our results report a general behaviour that is degraded as conditions approach to more realistic scenarios. However, our experiments also show that some methods are able to achieve a fairly similar performance to that of the non-distributed scenario. Thus, although there is a clear need for developing specific PS methodologies and algorithms for tackling these situations, those that reported a higher robustness against such conditions may be good candidates from which to start.

Realistic limits for subpixel movement detection

Object tracking with subpixel accuracy is of fundamental importance in many fields since it provides optimal performance at relatively low cost. Although there are many theoretical proposals that lead to resolution increments of several orders of magnitude, in practice this resolution is limited by the imaging systems. In this paper we propose and demonstrate through simple numerical models a realistic limit for subpixel accuracy. The final result is that maximum achievable resolution enhancement is connected with the dynamic range of the image, i.e., the detection limit is 1/2∧(nr.bits). The results here presented may aid in proper design of superresolution experiments in microscopy, surveillance, defense, and other fields.

LINDA (Line Drawing Analyzer) /

Originally presented as the author's thesis, University of Illinois at Urbana-Champaign.

Picture analysis by graph transformation,

"Supported in part by the Department of Computer Science and the Atomic Energy Commission under contract US AEC AT(11-1)2118."

Computer methods for analysis and synthesis of visual texture,

"C00-2118-0048."

SYM-1, a program that detects symmetry of variable-valued logic functions /

Mode of access: Internet.

Eidolyzer: a hardware realization of context-guided picture interpretation.

Cover title.

Methodological aspects of scene segmentation.

"COO-2118-0028."

Experiments with an image processing computer : part 3: proposed technical program, October 1, 1970 to September 30, 1971 /

"C00-1018-1213"--Cover.

Syntactic descriptions of pictures and Gestalt phenomena of visual perception.

Bibliography: leaf 25.

Synthesis of texture,

"Contract US AEC AT(11-1)2118."

The recursive nature of descriptions : a fixed point /

"UIUC-ENG-R-75-2539."

Texture analysis and cartographic feature extraction /

"January 1985."

Proceedings on "Emerging Patterns in AIPR". Abstracts

On cover, 1978 : NBS-EIA