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With the fast proliferation of multimedia and video display devices, searching and watching videos on the Internet has become an indispensable part of our daily lives. Many video-sharing web sites offer the service of searching and recommending videos from an exponentially growing repository of videos uploaded by individual users. The issue of finding videos suited to a user's personal preferences...
The task of dynamic hand gesture recognition includes several challenges arising due to variations in hand appearances, scale of the hand and the spatio-temporal variability of the gestures. To overcome these difficulties, in this work, we present a robust approach to detect and track a hand, and to recognize the hand trajectory based on DBNs (Deep Belief Networks) in conjunction with the SVM+HOG...
The task of indoor localization has been carried out with different approaches, which utilize data integrated from distinct sensors belonging to mobile devices. Floor determination is one of the crucial challenges encountered during indoor localization. The solutions to floor determination are mainly based on the techniques of Wireless Fingerprint and RFID (Radio Frequency Identification) sensors...
Considerable challenges arise in hand tracking due to background clutter, inconsistent lighting, scale changes, occlusions and total object disappearance. In order to cope with these difficulties, we present a robust hand tracker based on enhanced particle filters. To overcome the inherent shortcomings of the particle filter approach, we infuse it with the mean shift (CAMSHIFT) method, thereby reducing...
In this paper, we present a robust feature set to detect human hands in still images having simple as well as complex backgrounds. Our method relies on using a blend of existing and new shape-based, color-based and texture-based features. First, we identify the shortcomings of two existing features: Histograms of Oriented Gradient (HOG) and Color Name (CN). For HOG, we investigate the scenarios where...
To date, human hand detection in images remains a challenging task due to the variable lighting conditions, hand appearances and background noise. In this paper, we present an effective strategy based on feature fusion for detecting hands with cluttered surroundings. To form the fusions, we propose three novel noise invariant features, namely: 1) NCHOG (Noise Compensated Histogram of Oriented Gradients),...
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