Toby H. W. Lam

Gait flow image

In this paper, we propose a novel gait representation-gait flow image (GFI) for use in gait recognition. This representation will further improve recognition rates. The basis of GFI is the binary silhouette sequence. GFI is generated by using an optical flow field without constructing any model. The performance of the proposed representation was evaluated and compared with the other representations, such as gait energy image (GEI), experimentally on the USF data set. The USF data set is a public data set in which the image sequences were captured outdoors. The experimental results show that the proposed representation is efficient for human identification. The average recognition rate of GFI is better than that of the other representations in direct matching and dimensional reduction approaches. In the direct matching approach, GFI achieved an average identification rate 42.83%, which is better than GEI by 3.75%. In the dimensional reduction approach, GFI achieved an average identification rate 43.08%, which is better than GEI by 1.5%. The experimental result showed that GFI is stronger in resisting the difference of the carrying condition compared with other gait representations.

Human gait recognition by the fusion of motion and static spatio-temporal templates

In this paper, we propose a gait recognition algorithm that fuses motion and static spatio-temporal templates of sequences of silhouette images, the motion silhouette contour templates (MSCTs) and static silhouette templates (SSTs). MSCTs and SSTs capture the motion and static characteristic of gait. These templates would be computed from the silhouette sequence directly. The performance of the proposed algorithm is evaluated experimentally using the SOTON data set and the USF data set. We compared our proposed algorithm with other research works on these two data sets. Experimental results show that the proposed templates are efficient for human identification in indoor and outdoor environments. The proposed algorithm has a recognition rate of around 85% on the SOTON data set. The recognition rate is around 80% in intrinsic difference group (probes A-C) of USF data set.

A new representation for human gait recognition: motion silhouettes image (MSI)

Recently, gait recognition for human identification has received substantial attention from biometrics researchers. Compared with other biometrics, it is more difficult to disguise. In addition, gait can be captured in a distance by using low-resolution capturing devices. In this paper, we proposed a new representation for human gait recognition which is called Motion Silhouettes Image (MSI). MSI is a grey-level image which embeds the critical spatio-temporal information. Experiments showed that MSI has a high discriminative power for gait recognition. The recognition rate is around 87% in SOTON dataset by using MSI for recognition. The recognition rate is quite promising. In addition, MSI can also reduce the storage size of the dataset. After using MSI, the storage size of SOTON has reduced to 4.2MB.

iJADE FreeWalker – An Intelligent Ontology Agent-based Tourist Guiding System

Recently, Semantic Web has received substantial attention from the research community. Semantic web aims to provide a new framework that can enable knowledge sharing and resuing. Semantic Web is a collection of web technologies that include a number of markup languages such as RDF, OWL and RDFS. These markup languages are used for modeling a domain ontology. Ontology is defined as “a formal, explicit specification of a shared conceptualization”. By using ontology to model resources, humans and computers (software agents) can have a consensus on the resource structure. The use of these technologies allows the creation of a more effective web search system. In this book chapter, we modeled travel domain ontology by using Web Ontology Language (OWL). Instead of inviting an expert to model the ontology, we created the travel ontology by collecting and analyzing the structural information from a number of travel related websites. Besides, we implemented a tourist context-aware guiding system, iJADE FreeWalker, which is constructed by using Semantic Web technologies. iJADE FreeWalker integrates GPS, ontology and agent technologies to support location awareness for providing the precise navigation and classify the tourist information for the users. The system was tested on 30 novice users. 83% of the users felt that the system can help tourists find tourist information in Hong Kong. www.springerlink.com

Human Identification by Using the Motion and Static Characteristic of Gait

In this paper, we propose a gait recognition algorithm that fuses motion and static spatio-temporal templates of sequences of silhouette images, the motion silhouette contour templates (MSCTs) and static silhouette templates (SSTs). The performance of the proposed algorithm is evaluated experimentally using the SOTON dataset and the USF dataset. The proposed algorithm has a recognition rate of around 80% in intrinsic difference group (Probe A-C) of USF dataset which is 14% higher than the baseline algorithm

MASTER: AN INTELLIGENT ONTOLOGY-BASED MULTI-AGENT SYSTEM FOR SIGHTSEER

Recently, semantic web has received substantial attention from the research community. Semantic web aims to provide a new framework that can enable knowledge sharing and reusing. Semantic web is a collection of web technologies that include a number of markup languages such as RDF, OWL and RDFS. These markup languages are used for modeling a domain ontology. By using ontology to model resources, humans and computers (software agents) can have a consensus on the resource structure. The use of these technologies allows the creation of a more effective web search system. In this paper, we modeled travel domain ontology by using Web Ontology Language (OWL). Instead of inviting an expert to model the ontology, we created the travel ontology by collecting and analyzing the structural information from a number of travel related websites. Besides, we implemented an intelligent ontology-based Multi-Agent System for sighTseER (MASTER), which is constructed by using semantic web technologies. MASTER integrates Global Positioning System (GPS), ontology and agent technologies to support location awareness for providing the precise navigation and classify the tourist information for the users. The system was tested on 30 novice users. 83% of the users felt that the system can help tourists find tourist information in Hong Kong.

Modeling a personal profile by Fuzzy Ontology Map and its applications

Current ontology markup language, such as resource description framework (RDF) and web ontology language (OWL), supports modeling information with hard semantics. However, it is not possible for us to represent some uncertain information by using these standard modeling languages. We proposed an extension called fuzzy ontology map (FOM) which can be used to extend the current crisp ontology representations to model uncertain information. FOM was developed with strong mathematical basis. It is based on fuzzy theory and graph theory. In this paper, we presented the details about this fuzzy extension. In addition, we also showed how to adopt FOM for storing the personal profile information. This profile can provide enhanced functionalities for applications such as information filtering and personalization. At the end of this paper, we also presented an example application, CompBook, to show the idea how FOM profile works.

iJADE freewalker: an ontology-based tourist guiding system

In this paper, an ontology-based tourist guiding system, iJADE FreeWalker, is presented. The system integrated with agent and Semantic Web technologies to provide tourist information for the tourist. The tourist’s geographical information is gathered by GPS receiver. The GPS Agent migrates to the tourist information center and retrieves the related tourist information with respect to the user’s location. We defined an upper-level travel ontology by using Web Ontology Language (OWL). By using such system, tourists could browse the relevant information based on their interest and location.

Ontia iJADE: an intelligent ontology-based agent framework for semantic web service

The Internet becomes part of our lives. Users can access different kinds of information through the Internet. However, the exponential growth of the Internet led to a great problem: difficult to locate relevant information. The Semantic Web is an extension of the current web system in which information is organized in a well-defined manner and for enabling computers and people to work in cooperation. Agent technology gives a new way to this intelligent web system. In this paper, we proposed an innovative agent platform – Ontia iJADE which supports the Semantic Web Service. Ontia iJADE contains an ontology Server known as intelligent Java-based ontology Server (IJAOS), which stores and manages the ontology information for agents to share and reuse.

Silhouette spatio-temporal spectrum (SStS) for gait-based human recognition

Gait has received substantial attention from researchers. Different from other biometrics, gait can be captured in a distance and it is difficult to disguise. In this paper, we propose a feature template: Silhouette Spatio-temporal (SStS). It generates by concatenating silhouette projection vectors (SPV) which is formulated by projection of silhouette in vertical direction. We applied the Principle Component Analysis (PCA) for dimension reduction of the input feature space for recognition. The proposed algorithm has a promising performance, the identification rate is 95% in SOTON dataset and 90% CASIA dataset. Experiments showed that SStS has a high discriminative power and it is suitable for real-time gait recognition system.