Real-time multiple tracking using a combined technique

[[abstract]]This paper considers a real-time multi-object tracking algorithm for rigid and non-rigid objects. The major components of the tracking object system are extraction of the background image, adaptation of the background image, and identification of the extracted object. In each component, we improved existing methods without increasing the complexity of computation. The system was tested on our fish tank experiment that solves dynamic occlusions problems.[[sponsorship]]IEEE Computer Society Technical Committee on Distributed Processing (TCDP); Tamkung University[[notice]]補正完畢[[conferencetype]]國際[[conferencetkucampus]]淡水校園[[conferencedate]]20050328~20050330[[booktype]]紙本[[iscallforpapers]]Y[[conferencelocation]]臺北縣, 臺

Pose Estimation for Evaluating Standing Long Jumps via Dynamic Bayesian Networks

[[abstract]]A system is developed for analyzing poses in a standing long jump automatically. In the system, silhouette of the jumper is segmented from the background first. A thinning algorithm is then used to find a rough skeleton from the silhouette. Some image processing techniques are applied to make the resulted skeleton smoother and simpler. Key points are extracted from the skeleton. Finally, the dynamic Bayesian network (DBN) is used to determine the corresponding pose from the key points. The experimental result shows that pose estimation accuracy is quite good. According to the standing long jump standards, incorrect movements at different stages of the jump can thus be identified.[[conferencetype]]國際[[conferencedate]]20080617~20080620[[conferencelocation]]Beijing, Chin

Protein Crystallization Prediction with a Combined Feature Set

[[abstract]]Using X-ray crystallography to determine the 3D structure of a protein is a costly and time-consuming process. One of the major reasons is that the protein needs to be purified and crystallized first, and the failure rate of protein crystallization is quite high. Thus it is desired to use a computational method to predict protein crystallizability based on the primary structure information before the whole process starts. This can dramatically lower the average cost for protein structure determination. In this paper, we investigated the feature sets used in previous research. The support vector machine (SVM) was chosen as the predictor. Different weightings are set for the penalty parameters of the two classes to deal with the imbalanced data problem. As a result, a combined set of features is able to produce better results, especially on the specificity.[[conferencetype]]國際[[conferencedate]]20081216~20081218[[conferencelocation]]Al Ain, United Arab Emirate

Motion Analysis for the Standing Long Jump

[[abstract]]The standing long jump is a standard test for primary school students. It can be used to evaluate the development of basic sports skills of a child. This paper presents a system that can automatically detect the motion during a standing long jump from a video sequence. The silhouette of the jumper in the film is segmented from the background first for all frames. A stick model is applied to the silhouette found in the first frame. Then a GA-based search algorithm is used to find the stick models for the rest of the frames. The stick model points out the important joints of a person and can be used to represent the pose of the jumper in each frame. From the pose change in consecutive frames, we will be able to analyze the movement of the jumper.[[conferencetype]]國際[[conferencedate]]20060704~20060707[[conferencedate]]Lisboa, Portugal[[iscallforpapers]]

Posture Recognition with G-Sensors on Smart Phones

[[abstract]]With the popularity of smart phones in recent years, various sensors on smart phones can be utilized to detect the movement or intention of the smart phone users. In this research, we aim at using the signals collected from the G-sensor in the smart phone to recognize the posture of the user. Signals for sit, stand, walk and run are collected to train an offline neural network as the classifier. After the neural network learns the four postures, we then implement a neural network with the learned connection weights in a smart phone app. The app can record the postures of the user for the whole day and estimate the burned calories accordingly. This app can replace the pedometer to have a more accurate estimate of calorie consumption. Details of the app are presented in this paper. The accuracy of neural networks on posture recognition with G-sensor signals is also verified by five-fold cross-validation.[[conferencetype]]國際[[conferencedate]]20120926~20120928[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Melbourne, Australi

An RFID-Based Reminder System for Smart Home

[[abstract]]Some people tend to forget things when they leave home for work or school. It is desired that there would be a reminder system to automatically remind people what they might have forgotten to bring along just when they step outside their home. In this paper, we present a reminder system that uses the RFID technology to detect the objects that a user brings along. The system then provide a reminder object list to the user based on the history data collected from the same user and the events in the user's calendar on that day. The list is to remind the user objects he/she might have forgotten at home. A feedback mechanism is also designed to lower the possibility of unnecessary reminding. The user can mark the objects that are not needed from the reminder object list such that these objects will not appear in the list again in the same situation. A prototype system is introduced in this paper.[[conferencetype]]國際[[conferencedate]]20110322~20110325[[conferencelocation]]Singapore, Republic of Singapor

RFID-Based Personalized Behavior Modeling

[[abstract]]In this research, we aim at building an intelligent system that can detect abnormal behavior for the elderly at home. Deployment of RFID tags at home helps us collect the daily movement data of the elderly. The clustering technique is then used to build a personalized model of normal behavior based on these RFID data. After the model is built, any incoming datum outside the model can be seen as abnormal. In this paper, we present the design of the system architecture and show the preliminary results for data collection and preprocessing.[[conferencetype]]國際[[conferencedate]]20090707~20090709[[iscallforpapers]]Y[[conferencelocation]]Brisbane, Australi

Feature Selection for Cancer Classification on Microarray Expression Data

[[abstract]]Microarray is an important tool in gene analysis research. It can help identify genes that might cause various cancers. In this paper, we use feature selection methods and the support vector machine (SVM) to search for the disease-causing genes in microarray data of three different cancers. The feature selection methods are based on Euclidian distance (ED) and Pearson correlation coefficient(PCC). We investigated the effect on prediction results by training the SVM with different numbers of features and different kinds of kernels. The results show that linear kernel is the fittest kernel for this problem. Also, equal or higher accuracy can be achieved with only 15 to 100 features which are selected from 7129 or more features of the original data sets.[[conferencetype]]國際[[conferencedate]]20081126~20081128[[iscallforpapers]]Y[[conferencelocation]]Kaohsiung, Taiwa

Online Note Sharing in a Mobile Self-Guided Tour System

[[abstract]]This paper presents a self-guided tour system that allows a visitor to instantly share his/her notes or remarks about exhibits with others through the Internet. The note/remark not only can be stored with the exhibit information to be accessed by other visitors, but also can be broadcasted through microblogging in a timely manner. This provides an interaction mechanism for the visitor to feedback his/her remark on a certain exhibit to the administration and to share it with friends instantly. A prototype system for such an environment was realized through the RFID and mobile technologies. The architecture and the development of the prototype system are illustrated in this paper.[[conferencetype]]國際[[conferencedate]]20100215~20100218[[iscallforpapers]]Y[[conferencelocation]]Krakow, Polan