This paper has the capability to detect the person and follow that person by the surveillance mobile robot (ANT) in outdoor and indoor environment. Monocular based vision tracking technique used in the paper and following method used for surveillance robot is proposed, as it combines face detection, person’s upper body features extraction and Moment calculation modules proposed in this paper. W...

This paper considers ways in which a person can cue and constrain an artificial agent’s attention to salient features. In one experiment, a person uses gestures to direct an otherwise autonomous robot hand through a known task. Each gesture instantiates the key spatial and intentional features for the task at that moment in time. In a second experiment, which is work in progress, a person will ...

How does one recognize a person when face identification fails? Here, we show that people rely on the body but are unaware of doing so. State-of-the-art face-recognition algorithms were used to select images of people with almost no useful identity information in the face. Recognition of the face alone in these cases was near chance level, but recognition of the person was accurate. Accuracy in...

The performance of face recognition and/or authentication systems is greatly affected by within-person variations encountered in human faces. Within person facial variations distort the appearance of faces leading to inconsistencies between facial features stored in templates and features derived from a face, of the corresponding subject, captured at a different instance. For this reason a cons...

This paper presents an RGB-D based human re-identification approach using novel biometrics features from the body’s volume. Existing work based on RGB images or skeleton features have some limitations for realworld robotic applications, most notably in dealing with occlusions and orientation of the user. Here, we propose novel features that allow performing re-identification when the person is ...

In this paper we describe our participation in the SIGHAN 2010 Task3 (Person Name Disambiguation) and detail our approaches. Person Name Disambiguation is typically viewed as an unsupervised clustering problem where the aim is to partition a name’s contexts into different clusters, each representing a real world people. The key point of Clustering is the similarity measure of context, which dep...

Named Entity Recognition is an information extraction technique that identifies name entities in a text. Three popular methods have been conventionally used namely: rule-based, machine-learning-based and hybrid of them to extract named entities from a text. Machine-learning-based methods have good performance in the Persian language if they are trained with good features. To get good performanc...

In video surveillance, person re-identification (re-id) is probably the open challenge, when dealing with a camera network with non-overlapped fields of view. Re-id allows the association of different instances of the same person across different locations and time. A large number of approaches have emerged in the last five years, often proposing novel visual features specifically designed to h...

The human face is an attractive biometric identifier and face recognition has certainly improved a lot since its beginnings some three decades ago, but still its application in real world has achieved limited success. In this doctoral dissertation we focus on a local feature of the human face namely the lip and analyse it for its relevance and influence on person recognition. In depth study is ...

This article presents studies of Hindi that investigate whether responses to syntactic agreement violations vary as a function of the type and number of incorrect agreement features, using both electrophysiological (ERP) and behavioral measures. Hindi is well suited to investigation of this issue, since verbs in Hindi mark agreement with the person, number, and gender features of the nominative...