Unsupervised Segmentation of Stereoscopic Video Objects: Constrained Segmentation Fusion Versus Greedy Active Contours

In this paper, we present a novel memory access reduction scheme (MARS) for two-dimension fast cosine transform (2-D FCT). It targets programmable DSPs with high memory-access latency. It reduces the number of memory accesses by: 1) reducing the number of weighting factors and 2) combining butterflies in vector-radix 2-D FCT pruning diagram from two stages to one stage with an efficient structure. Hardware platform based on general purpose processor is used to verify the effectiveness of the proposed method for vector-radix 2-D FCT pruning implementation. Experimental results validate the benefits of the proposed method with reduced memory access, less clock cycle and fewer memory space compared with the conventional implementation.     

Web Access to Large Audiovisual Assets Based on User Preferences

Current multimedia databases contain a wealth of information in the form of audiovisual as well as text data. Even though efficient search algorithms have been developed for either media, there still exists the need for abstract presentation and summarization of the results of database users' queries. Moreover, multimedia retrieval systems should be capable of providing the user with additional information related to the specific subject of the query, as well as suggest other topics which could be identified to attract the interest of users with a similar profile. In this paper, we present solutions to these issues, giving as an example an integrated architecture we have developed, along with notions that support efficient and secure Internet access to audiovisual/video databases. Segmentation of each video in shots is followed by shot classification in a number of predetermined categories. Generation of users' profiles according to the categories, enhanced by relevance feedback, permits an efficient presentation of retrieved video shots or characteristic frames in terms of the user interest in them. Moreover, this clustering scheme assists the notion of lateral links that enable the user to continue retrieval with data of similar nature or content to those already returned. Furthermore, user groups are formed and modeled by registering actual preferences and practices. This enables the system to predict information that is possibly relevant to the user's interest and present it along with the returned results. The concepts utilized in this system can be smoothly integrated in MPEG-7 compatible multimedia database systems.     

An efficient fully unsupervised video object segmentation scheme using an adaptive neural-network classifier architecture

In this paper, an unsupervised video object (VO) segmentation and tracking algorithm is proposed based on an adaptable neural-network architecture. The proposed scheme comprises: 1) a VO tracking module and 2) an initial VO estimation module. Object tracking is handled as a classification problem and implemented through an adaptive network classifier, which provides better results compared to conventional motion-based tracking algorithms. Network adaptation is accomplished through an efficient and cost effective weight updating algorithm, providing a minimum degradation of the previous network knowledge and taking into account the current content conditions. A retraining set is constructed and used for this purpose based on initial VO estimation results. Two different scenarios are investigated. The first concerns extraction of human entities in video conferencing applications, while the second exploits depth information to identify generic VOs in stereoscopic video sequences. Human face/ body detection based on Gaussian distributions is accomplished in the first scenario, while segmentation fusion is obtained using color and depth information in the second scenario. A decision mechanism is also incorporated to detect time instances for weight updating. Experimental results and comparisons indicate the good performance of the proposed scheme even in sequences with complicated content (object bending, occlusion).     

Human action annotation,modeling and analysis based on implicit user interaction

This paper proposes an integrated framework for analyzing human actions in video streams. Despite most current approaches that are just based on automatic spatiotemporal analysis of sequences, the proposed method introduces the implicit user-in-the-loop concept for dynamically mining semantics and annotating video streams. This work sets a new and ambitious goal: to recognize, model and properly use “average user’s” selections, preferences and perception, for dynamically extracting content semantics. The proposed approach is expected to add significant value to hundreds of billions of non-annotated or inadequately annotated video streams existing in the Web, file servers, databases etc. Furthermore expert annotators can gain important knowledge relevant to user preferences, selections, styles of searching and perception.     

CNC micromilling properties and optimization using genetic algorithms

Micromachining operations are mainly restricted to precision machining of two-dimensional microparts, usually performed on microelectrical discharge machining or microlaser computer numerical control (CNC) machine tools. However, micromilling can fully exploit computer-aided design/computer-aided manufacturing (CAM) software abilities, in order to achieve more complex three-dimensional micropart geometries. After fully defining the micromilling process parameters and related constraints, optimization methodologies, such as genetic algorithms, can be coupled with CAM software, thus obtaining optimal process parameters with very small calculation cost. In this study, CNC micromilling process is systematically presented, along with respective micromilling tools and the necessary industrial equipment for the processes. Genetic algorithm code was developed in Visual Basic, which optimizes the process and ultimately yields optimal parameter values, including all process particulars. Two test cases were presented, and results were discussed in terms of micropart quality, production time, and calculation cost.