Tekoing Lim

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We present the LaRED, a <i>Large R</i>GB-D <i>E</i>xtensible hand gesture <i>D</i>ataset, recorded with an Intel's newly-developed short range depth camera. This dataset is unique and differs from the existing ones in several aspects. Firstly, the large volume of data recorded: 243, 000 tuples where each tuple is composed of a color image, a depth image,(More)
There are two main problems that make hand gesture tracking especially difficult. One is the great number of degrees of freedom of the hand and the other one is the rapid movements that we make in natural gestures. Algorithms based on minimizing an objective function, with a good initialization, typically obtain good accuracy at low frame rates. However,(More)
Developing automatic facial age estimation algorithms that are comparable or even superior to the human ability in age estimation becomes an attractive yet challenging topic emerging in recent years. The conventional methods estimate one person’s age directly from the given facial image. In contrast, motivated by human cognitive processes, we proposed a(More)
Ranking algorithms have proven the potential for human age estimation. Currently, a common paradigm is to compare the input face with reference faces of known age to generate a ranking relation whereby the first-rank reference is exploited for labeling the input face. In this paper, we proposed a framework to improve upon the typical ranking model, called(More)
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