Signal and Data Processing

Abstract: Nowadays, the animators give life to the fancy characters by making natural movements to organs of cartoon characters. To achieve this goal, movements of living individuals can be applied into cartoon characters. In this paper, a skeletal correspondence finding based method is proposed to transfer movement of a 2D character into a new character, where these two shapes have the same structural topology, approximately. Based on the given animation sequence of source character, each body part of this character is segmented according to a specific motion. In this case, an exact skeleton with defined joints will be achieved for source shape. The target character skeleton is obtained by automatic skeleton extraction algorithms. In this stage, by skeletal correspondence finding between source and target character, we can transfer skeleton deformation of each source body parts into target body parts. This deformation contains the values of skew, scale and orientation that are achieved from reference pose and deformed poses of source skeletons. Finally, to evaluate the proposed method efficiency, we perform it on 2D animation characters. The achieved results illustrate the ability of the algorithm in generating correct and natural motions for different variety of characters. The method is robust to the type of characters and can transfer variety of deformations.

Deductive Database systems are designed based on a logical data model. Data (as opposed to Relational Databases Management System (RDBMS) in which data stored in tables) are saved as facts in a Deductive Database system. Datalog Educational System (DES) is a Deductive Database system that Datalog mode is the default mode in this system. It can extract data to use outer joins with three query languages (Datalog, SQL and RA) in default mode. In 2004, system DES was designed and implemented by Fernando S´aenz-P´erez from Department of Artificial Intelligence and Software Engineering, Complutense University, Madrid, Spain. In a paper, this researcher introduced outer joins of system DES  in 2012. The most important objective of present research is to complement and extend the paper authored by mentioned researcher. Therefore, in prior research, choosing the most appropriate query language has not been investigated to use outer joins for data extraction in Datalog mode in DES system. In this study, by considering two parameters (cost of writing a query and memory usage of a query) choosing the most appropriate query language has been investigated to use outer joins for data extraction in Datalog mode in Deductive system DES. Cost of writing a query parameter is considered in this study to decrease the query typing time, but other parameters are related to the query processing are not considered. If the processing time of the three query languages is assumed identical, after entering the query in the system DES, the idea of the present study (reduction of the typing time) can lead to the reduction of the response time. Also, there are two hypotheses in this study as follows: 1) it is assumed that the user is fluent in all three query languages and wants to access the given data quickly through the most appropriate query language. 2) In the present study, the simplicity or difficulty of a query language is not considered. The results of the research show that one language cannot be appropriate for all queries; therefore, for every different query the most appropriate query language must be chose to use outer joints. In the current research, the most appropriate query language is the one in which, in comparison with other two query languages, the user will need to use less buttons of the keyboard to press in order to fulfill the query. The decrease in the number of buttons pressed by the user will decrease the time consumed to fulfill the query and, therefore, it will lead to a faster access to data.