An active contour model Snake and its modifications are widely used for image analysis and computer vision problems, especially for object contour extraction. To overcome some drawbacks associated with existing active contour models used for object contour extraction, this paper presents a shape-constraint-based active contour model (SC-ACM) which uses information of the contour shape of the target object to constrain the snake and controls the snake shape when the snake moves at every step, where the object contour shape is assumed to be roughly known a priori. Successful application of the SC-ACM to extraction of contours on real and synthetic images demonstrates its effectiveness.
The amount of contents we can obtain through TV broadcasting by satellite, CATV, and the Internet is increasing day by day. In this paper, we propose a method and an application for future Interactive TV service, called ADTV. In our method, users not only get information about specific video objects, but they can describe video objects about them using the incomplete description of portion in each frame. We discuss automatic structuring of video objects automatically using incomplete description. We implement the prototype system to provide users with some basic functions such as “Description”, “Question and Answer”, and “Retrieval” regarding real-world video based on digital maps. The system can link video objects to digital maps so that users can retrieve an image of a building or get information about an unknown building in a video.
It is important to structure video sequences for efficiently editing and indexing the images that may be requested from an enormous volume of video data. One approach to structuring is to divide a series of images into fixed units such as cut points or camera work, and then retrieving against the units. This paper proposes a method of automatically extracting camera work sequences. Specifically, in this paper, MPEG2, which can be mainstream in future, coded video data is targeted. To reduce the volume of data to be processed, to eliminate the time need for decoding, and to avoid video loss due to decoding, we estimate the camera work using the extracted motion vectors which used in the motion compensation process. The proposed method extracts the motion vectors using motion compensation. To recognize the camera work in each frame, we also present an algorithm for extracting each camera work sequence. The efficiency of the method is confirmed using MPEG2 coded image data of diverse test video sequences.
This paper describes the design and implementation of an accelerated Global Positioning System (GPS) navigation program for a 32-bit embedded microcontroller unit without a floating-point processing unit. By optimizing the software floating-point library, introducing a new floating-point format and improving the math functions, the new GPS navigation program saves about 90% of the execution time compared to that implemented by a GNU C compiler and the precision is degraded by only 0.6%.