graph of words, a related image. It allows a user to generate Changing between frames is one of the most obvious informa-queries containing both temporal and spatial concepts, and tion in video data. This frame-by-frame time series data is also provides content-based searching. However, how to essential to many application areas. However, how to extract extract and compare video contents in a video information and compare video contents in a video information system is system is still an important problem to be solved.
still an important problem to be solved. In this paper, we focus
Therefore, the problem we deal with is the design of a on the problem of design a fast searching method in a video video information system with an efficient video content information system to locate video segments that match a conrepresentation, an effective multilevel query processing tent-based query, approximately by time series feature values. capability, and a fast searching method. According our The idea is to extract video contents via low-level feature extracresearches, frame-to-frame object changing is one of the tion and/or high level semantic retrieval mechanisms according most obvious information in video data. With temporal to a specific point of view, then segment video contents into bounding boxes via a box segmentation mechanism by their extension, frame-to-frame object changing cause a series time series feature values. Video content indexing is constructed of frame-by-frame data. This frame-by-frame time series by the characteristics of prominent points that accompany data is essential to many areas, such as gesture recognition bounding boxes. We also propose an efficient and effective in human-centered information systems, dynamic indusvideo content matching algorithm to find similar sequences. trial processed monitoring, scene segmentation [1, 2], auto-With the help of the video indexing and matching mechanisms, matic object tracking, and dynamic scene understanding. several high level box-to-box and low level point-to-point query That is, the searching method should include an indexing
types can be requested. The implementation and performance and a matching mechanism that can search a video informaevaluation of our video information prototype system is tion system by time-series feature values or even by multidescribed. Β© 1997 Academic Press level semantic meanings, in order to locate video subsequences that match a query sequence approximately.
1. Introduction
Furthermore, time-series data indexing and matching mechanism can also be applied to many other applications, such as banking, policy decisions, inventory control, and Due to advances in data acquisition and computer techscientific databases, where the history and prediction are nologies, many new applications involving the video inforimportant. mation retrieval system are emerging. Video is a medium
In current video database systems, only fundamental with high complexity. It has temporal and spatial charactertechniques, such as keyword-based searching [3], hierarchiistics. Information related to position, timing, distance, cal video icon browsing and indexing [4], are provided. temporal and spatial relationships are included in video Most of the previous researches in video data are focused data implicitly. Also, a variety of statistical features is conon motion and scene analysis. Very little work has been tained in a video frame, such as object color, shape, and done on the design of index structures that combine spatial location.
and temporal attributes for video databases. In order to manage information in video data, a video information system must be provided. A number of special
In this paper, we provide several algorithms to solve these indexing and content-based matching problems. In requirements distinguish the video information system design approach from traditional databases. A video informa-Section 2, we describe a generic architecture of a contentbased video information system, and survey some of the tion system needs complex structural representation of its multilevel contents. Video content in a video information research projects relevant to our work. In Section 3, we define the video representation and evaluation model for system can be represented as a text-type keyword, a para-107