This paper proposes the automatic annotation of sports video for content-based retrieval. Conventional methods using position information of objects such as locus, relative positions, their transitions, etc., as indices, have drawbacks that tracking errors of a certain object due to occlusions causes recognition failures, and that representation by position information essentially has a limited number of recognizable events in the retrieval. Our approach incorporates human behavior analysis and specific domain knowledge with conventional methods, to develop an integrated reasoning module for richer expressiveness of events and robust recognition. Based on the proposed method, we implemented a content-based retrieval system which can identify several actions on real tennis video. We select court and net lines, players' positions, ball positions, and players' actions, as indices. Court and net lines are extracted using a court model and Hough transforms. Players and ball positions are tracked by adaptive template matching and particular predictions against sudden changes of motion direction. Players' actions are analyzed by 2D appearance-based matching using the transition of players' silhouettes and a hidden Markov model. The results using two sets of tennis video is presented, demonstrating the performance and the validity of our approach.

The estimation of the parameters of a projective transformation that relates the coordinates of two image planes is a standard problem that arises in image and video mosaicking, virtual video, and problems in computer vision. This problem is often posed as a least squares minimization problem based on a finite set of noisy point samples of the underlying transformation. While in some special cases this problem can be solved using a linear approximation, in general, it results in an 8-dimensional nonquadratic minimization problem that is solved numerically using an 'off-the-shelf' procedure such as the Levenberg-Marquardt algorithm. We show that the general least squares problem for estimating a projective transformation can be analytically reduced to a 2-dimensional nonquadratic minimization problem. Moreover, we provide both analytical and experimental evidence that the minimization of this function is computationally attractive. We propose a particular algorithm that is a combination of a projection and an approximate Gauss-Newton scheme, and experimentally verify that this algorithm efficiently solves the least squares problem.

This paper is concerned with the efficient temporal propagation of correspondences between frames of two video sequences, an integral component of many video processing tasks. The main contribution is a framework for the recursive propagation of these correspondences. The propagation consists of a time update step and a measurement update step. The time update depends only on the dynamics of the rotating source cameras, while the measurement update can be tailored to any member of a general class of image correspondence algorithms. Using these results, the correspondence between points of each frame pair can be propagated and updated in a fraction of the time required to estimate correspondences anew at every frame. We discuss an application of the recursive correspondence propagation framework to the creation of virtual video. Previous virtual view algorithms have been used to generate synthetic video of a static scene, in which objects seem frozen in time. In contrast, the algorithms described here allow the creation of "true" virtual video, in the sense that the synthetic video evolves dynamically along with the scene. While virtual video is our motivating application, the recursive correspondence propagation framework applies to any two-camera video application in which correspondence is difficult and prohibitively time-consuming to estimate by processing frame pairs independently.

A visual tracking system is presented in which a combination of techniques is used to obtain motion features of objects from a video sequence. Further processing of the motion features gives the spatio-temporal trajectories of the objects, that can be used as cues for annotation. The system solves problems found in tracking objects in unconstrained environments, such as in sports games, where there are multiple objects in motion, the camera performs pan, tilt and zoom movements, and there are objects other than the players in the background. Coarse segmentation is performed with multi-class statistical color models, constructed from samples of the representative colors of each team. Motion vectors are computed to find region correspondence between consecutive frames. Background elements are eliminated by using camera motion parameters, and other false matches are detected by analyzing motion pattern consistency. Finally, objects are registered by placing windows centered in each tracked region. An experimental realization was used to test the system for tracking players in a soccer game, but it could had also been used for generating annotation cues of videos from other sports as well.

The paper presents an approach for region based video mosaicing, treating moving objects separately from the background, and with improved ghost-like noise elimination. The mosaic images show the moving objects superimposed over a stationary background. Conventional technologies can reduce the ghost-like noise that occurs from moving objects by using temporal median filtering, but its efficiency depends on the ratio between the speeds of the camera and the moving object. Our technology eliminates these noises more efficiently by using segmented images of a spatio-temporal video sequence. Segmentation is performed using a novel technique that uses different configurations of quad-trees for the initial separation in the split-and-merge process. The segmented images are also used to display tracked moving objects on the panoramic image.

In this paper we present a method for representing and retrieving video sequences based on the domain-specific behavior of objects present in the scenes. The representation includes three parts: (a) Action description, representing the action performed by a single object. (b) Interaction description, which describes interactions between multiple objects and is mapped directly to the event semantics in the content domain. (c) Event Structure, which provides a set of spatial and temporal relationship functions, along with a syntax to define the necessary conditions that a particular interaction should meet. Retrieval is performed by processing Event Structures, interpreting object relationships and selecting the relevant combinations of Action descriptions which match the conditions defined in the Event Structures. We describe an implementation of this system for retrieving scenes of soccer plays from among several soccer video sequences.

The objective of this paper is to propose a method to automatically detect spicule shadows in mammograms. The method is consisted of two steps, enhancement and feature selection. First, spicule shadows are enhanced by using a newly developed operation. An opening operation is applied to remove noises and a direction map is made for feature selection. Second, a concentration expression is given with gray levels and two features are selected for recognition of tumors with spicules. In the method, the direction of spicules is not only considered, but the density is also utilized for classification of tumors with spicules. The method was tested on 24 samples including seven tumors with spicules. The recognition rate for tumors with spicules was 100% without the false positives.

An ATM (asynchronous transfer mode) network architecture for supporting connectionless service aimed at inter-LAN communication and high-performance distributed applications is presented. Two service scenarios, the related reference configuration, and a possible internetwork scenario for supporting the connectionless mode terminal are presented. A discussion is also presented of addressing and routing schemes and the two types of cell transport methods proposed for interconnection between the customer premises network and the connectionless service function (CLSF) located within the ATM network. The appropriate solutions for the cell transport methods are shown. As an application of the ATM connectionless service, a description is given of the gateway architecture supporting the inter-LAN communication via the CLSF.>