Nikolaos Papanikolopoulos

A near-infrared fusion scheme for automatic detection of vehicle passengers

We undertook a study to determine if the automatic detection and counting of vehicle passengers is feasible. An automated passenger counting system would greatly facilitate the operation of freeway lanes reserved for car-pools (HOV lanes). In the present paper we report our findings regarding the appropriate sensor phenomenology and arrangement for the task. We propose a novel system based on fusion of near-infrared imaging signals and we demonstrate its adequacy with theoretical and experimental arguments.

An on-line handwritten note recognition method using shape metamorphosis

We propose a novel user-dependent method for the recognition of on-line handwritten notes. The method employs as a dissimilarity measure the degree of morphing between an input curve and a template curve. A physics-based approach substantiates the degree of morphing as a deformation energy and casts the problem as an energy minimization problem. The method operates upon key segmentation points that are provided by an appropriate segmentation algorithm. The segmentation objective is not to locate letters, but instead to locate corners and some key low curvature points (an easier task). This is part of the methods strategy to see the word as a generic on-line curve. Due to this strategy, the proposed method can handle collectively both cursive words and hand-drawn line figures, the two key ingredients of handwritten notes. Most importantly, the proposed system achieves high recognition rates without ever resorting to statistical models.

A ground truth tool for Synthetic Aperture Radar (SAR) imagery

The performance of computer vision algorithms has made great strides and it is good enough to be useful in a number of civilian and military applications. Algorithm advancement in Automatic Target Recognition (ATR) in particular; has reached a critical point. State-of-the-art ATRs are capable of delivering robust performance for certain operational scenarios. As Computer Vision technology matures and algorithms enter the civilian and military marketplace as products, the lack of a formal testing theory and tools become obvious. In this paper we present the design and implementation of a Ground Truth Tool (GTT) for Synthetic Aperture Radar (SAR) imagery. The tool serves as part of an evaluation system for SAR ATRs. It features a semi-automatic method for delineating image objects that draws upon the theory of deformable models. In comparison with other deformable model implementations, our version is stable and is supported by an extensive Graphical User Interface (GUI). Preliminary experimental tests show that the system can substantially increase the productivity and accuracy of the image analyst (IA).