• Journal of the HCI Society of Korea
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• v.10 no.2
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• pp.45-55
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• 2015

In recent years, keypoint recognition and tracking technologies are considered as crucial task in many practical systems for markerless augmented reality. The keypoint recognition and technologies are widely studied in many research areas, including computer vision, robot navigation, human computer interaction, and etc. Moreover, due to the rapid growth of mobile market related to augmented reality applications, several effective keypoint-based matching and tracking methods have been introduced by considering mobile embedded systems. Therefore, in this paper, we extensively analyze the recent research trends on keypoint-based recognition and tracking with several core components: keypoint detection, description, matching, and tracking. Then, we also present one of our research related to mobile augmented reality, named mobile tour guide system, by real-time recognition and tracking of tour maps on mobile devices.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.192-197
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• 2017

In this paper, image filter optimization method based on common sub-expression elimination is proposed for low-power image feature extraction hardware design. Low power and high performance object recognition hardware is essential for industrial robot which is used for factory automation. However, low area Gaussian gradient filter hardware design is required for object recognition hardware. For the hardware complexity reduction, we adopt the symmetric characteristic of the filter coefficients using the transposed form FIR filter hardware architecture. The proposed hardware architecture can be implemented without degradation of the edge detection data quality since the proposed hardware is implemented with original Gaussian gradient filtering algorithm. The expremental result shows the 50% of multiplier savings compared with previous work.