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Hand gesture based human–computer interaction with mobile phones heavily relies on robust hand detection. Because of the limited computational resources of mobile phones, computationally complex algorithms are infeasible. In this paper, we discover that: though traditional frame difference based methods are computationally inexpensive, they have the following problems in many situations: (1) may completely...
In this paper, we propose a novel solution of anomaly detection in crowd scene by jointly modeling appearance and dynamics of motion. First, a novel high-frequency feature based on optical flow (HFOF) is introduced. It can well capture the dynamic information of optical flow. Besides, we adopt the other two types of features, namely multi-scale histogram of optical(MHOF), and dynamic textures (DT)...
Selective sampling has been widely used in relevance feedback of image retrieval to alleviate the burden of labeling by selecting the most informative instances for user to label. Traditional sample selection scheme often selects a batch of instances each time and label them simultaneously, which ignores the correlation among instances and results in redundant labeling. In this paper, we propose an...
Behavior analysis across multi-cameras becomes more and more popular with the rapid development of camera network in video surveillance. In this paper, we propose a novel unsupervised graph matching framework to associate trajectories across partially overlapping cameras. Firstly, trajectory extraction is based on object extraction and tracking and is followed by a homographic projection to a mosaic-plane...
In this paper, a modified Neural Gas algorithm is proposed and used to approximate hand topology. As original Neural Gas algorithm is intractable for real-time applications, some optimization such as unnecessary adaption removal and simple learning rate function are introduced to make it applicable for real-time applications. With segmented hand area, the topology representation can be obtained based...
This paper presents a robust hand gesture analysis method using 3D depth data. Our scheme focuses on accurate hand segmentation by eliminating the negative effect of the forearm part. In the general human computer interaction (HCI) tasks, such an assumption usually holds that the depth of hand is smaller than forearm. Therefore, the precise hand region can be obtained through the fusion of the hand...
As an emerging human-computer interaction approach vision based hand interaction is more natural and efficient. However in order to achieve high accuracy, most of the existing hand posture recognition methods need a large number of labeled samples which is expensive or unavailable in practice. In this paper, a co-training based method is proposed to recognize different hand postures with a small quantity...
Information overload has become an important problem in the Internet, and that all kinds of existing ads flood into peoplepsilas eyes causes scarcity of userpsilas attention. To provide relevant information under userpsilas control, we propose an online video advertising framework based on userpsilas attention relevancy computing. Users receive relevant video ads in exchange of their attention consumption...
Hand gesture has been used as a natural and efficient way in human computer interaction. Due to independence of auxiliary input devices, vision-based hand interfaces is more favorable for users. However, the process of hand gesture recognition is very time consuming, which often brings much frustration to users. In this paper, we propose a fast feature detection and description approach which can...
Compared with the traditional interaction approaches, such as keyboard, mouse, pen, etc, vision based hand interaction is more natural and efficient. In this paper, we proposed a robust real-time hand gesture recognition method. In our method, firstly, a specific gesture is required to trigger the hand detection followed by tracking; then hand is segmented using motion and color cues; finally, in...
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