Gyeonghoon Kim

Learn More
Moving object recognition in a video stream is crucial for applications such as unmanned aerial vehicles (UAVs) and mobile augmented reality that require robust and fast recognition in the presence of dynamic camera noise. Devices in such applications suffer from severe motion/camera blur noise in low-light conditions due to low-sensitivity CMOS image(More)
Object recognition processors have been reported for the applications of auto-nomic vehicle navigation, smart surveillance and unmanned air vehicles (UAVs) [1-3]. Most of the processors adopt a single classifier rather than multiple clas-sifiers even though multi-classifier systems (MCSs) offer more accurate recognition with higher robustness [4]. In(More)
—A hybrid radix-4/-8 multiplier is proposed for portable multimedia applications that demand high speed and low energy operation. Depending on the input pattern, the multiplier operates in the radix-8 mode in 56% of the input cases for low power, but reverts to the radix-4 mode in 44% of the slower input cases for high speed. For this, a mode detection(More)
—A heterogeneous multi-core processor is proposed to achieve real-time dynamic object recognition on HD 720p video streams. The context-aware visual attention model is proposed to reduce the required computing power for HD object recognition based on enhanced attention accuracy. In order to realize real-time execution of the proposed algorithm, the(More)