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Three-dimensional gaging involves the measurement and mapping of 3-D surfaces. Gaging accuracy depends on measurement accuracy in the images, image scale, and stereo geometry. Multiple cameras are often needed to provide adequate stereoscopic coverage of the object. This paper reports on an automatic 3-D gaging system that is being developed at the University of Illinois at Urbana-Champaign. A portable 3-D target field, consisting of 198 targets each identified with a bar code, is used to determine the interior and exterior orientation parameters of each camera. Image-processing algorithms have been developed to identify conjugate image points in stereo pair of images, and the object-space coordinates of these points are computed by stereo intersection. Software has also been developed for analysis and data editing.

Content-based image retrieval (CBIR) has become one of the most active research areas in the past few years. Most of the attention from the research has been focused on indexing tech- niques based on global feature distributions. However, these global distributions have limited discriminating power because they are un- able to capture local image information. The use of interest points in content-based image retrieval allow image index to represent local properties of the image. Classic corner detectors can be used for this purpose. However, they have drawbacks when applied to vari- ous natural images for image retrieval, because visual features need not be corners and corners may gather in small regions. In this paper, we present a salient point detector. The detector is based on wavelet transform to detect global variations as well as local ones. The wavelet-based salient points are evaluated for image retrieval with a retrieval system using color and texture features. The results show that salient points with Gabor feature perform better than the other point detectors from the literature and the randomly chosen points. Significant improvements are achieved in terms of retrieval accuracy, computational complexity when compared to the global feature approaches. © 2001 SPIE and IS&T. (DOI: 10.1117/1.1406945)

GPS‐guided stereo, solid‐state camera systems can perform real‐time surveying and mapping functions that are vital to the automation of many engineering processes. While GPS provides point positioning of the cameras in real time, a stereo vision system can perform 3‐D mapping of the scene, as well as recognition and location of survey targets. GPS has already demonstrated the positioning accuracy required for such a system. Vision systems with pointing accuracy of ±1sec of arc or better have also been built. Current research and developments in vision systems for surveying are cited. Two conceptual applications of GPS‐guided vision systems are given.

Recognizing human facial expression and emotion by computer is an interesting and challenging problem. In this paper we propose a method for recognizing emotions through facial expressions displayed in video sequences. We introduce the Cauchy Naive Bayes classifier which uses the Cauchy distribution as the model distribution, and provide a framework for choosing the best model distribution assumption. Our person-dependent and person-independent experiments show that the Cauchy distribution assumption typically provides better results than the Gaussian distribution assumption.

In human computer interaction, the ultimate goal is to have effortless and natural communication. In the research literature significant effort has been directed toward understanding the functional aspects of the communication. However, it is well known that the functional aspect is insufficient for natural interactions. Indeed, the emotional or affective aspect has been shown in the psychology literature to be at least if not more important. As emotional beings, we interact most comfortably with other emotional beings. We give an overview of our current research toward automatic recognition of human emotions.

Welcome, friends and colleagues. Just one decade in the past would show our field as being composed of a few scattered workshops. Since then there has been tremendous growth in both research and applications. In the past 4 years, as a community we have published over a 1,000 peer reviewed research papers in areas ranging from image and audio retrieval to scientific and medical image search. We have developed our own test sets, software libraries, evaluation benchmarks, workshops and major conferences (notably ICMR, CIVR, and MIR). Only one important piece was missing to make the picture complete: a research journal. Now, it is my pleasure to introduce the first journal focused on our field, The International Journal of Multimedia Information Retrieval (IJMIR). Our new journal encompasses all topics related to retrieval, exploration, and mining of media databases and collections. It combines the vibrant areas related to retrieval of images, audio, video, and medical and scientific imagery with understanding of the human side of the system including the social aspects which are crucial to interactive search. An unarguable strength of our field is that it plays an important role in diverse scientific areas because many significant recent discoveries have been made through analyzing and searching local and international imaging databases. In our journal, there are essentially two paper categories: regular papers (original research) and surveys. Regular papers are typically triple peer reviewed and are meant to represent the novel research from the community. Surveys undergo a peer review from a senior community member and are meant to capture trends, illuminate critical problems, and give insight into the state-of-the-art. In