Byung Chang Kang

Real-Time Gesture Interface Based on Event-Driven Processing From Stereo Silicon Retinas

We propose a real-time hand gesture interface based on combining a stereo pair of biologically inspired event-based dynamic vision sensor (DVS) silicon retinas with neuromorphic event-driven postprocessing. Compared with conventional vision or 3-D sensors, the use of DVSs, which output asynchronous and sparse events in response to motion, eliminates the need to extract movements from sequences of video frames, and allows significantly faster and more energy-efficient processing. In addition, the rate of input events depends on the observed movements, and thus provides an additional cue for solving the gesture spotting problem, i.e., finding the onsets and offsets of gestures. We propose a postprocessing framework based on spiking neural networks that can process the events received from the DVSs in real time, and provides an architecture for future implementation in neuromorphic hardware devices. The motion trajectories of moving hands are detected by spatiotemporally correlating the stereoscopically verged asynchronous events from the DVSs by using leaky integrate-and-fire (LIF) neurons. Adaptive thresholds of the LIF neurons achieve the segmentation of trajectories, which are then translated into discrete and finite feature vectors. The feature vectors are classified with hidden Markov models, using a separate Gaussian mixture model for spotting irrelevant transition gestures. The disparity information from stereovision is used to adapt LIF neuron parameters to achieve recognition invariant of the distance of the user to the sensor, and also helps to filter out movements in the background of the user. Exploiting the high dynamic range of DVSs, furthermore, allows gesture recognition over a 60-dB range of scene illuminance. The system achieves recognition rates well over 90% under a variety of variable conditions with static and dynamic backgrounds with naïve users.

Touchless hand gesture UI with instantaneous responses

In this paper we present a simple technique for real-time touchless hand gesture user interface (UI) for mobile devices based on a biologically inspired vision sensor, the dynamic vision sensor (DVS). The DVS can detect a moving object in a fast and cost effective way by outputting events asynchronously on edges of the object. The output events are spatiotemporally correlated by using novel event-driven processing algorithms based on leaky integrate-and-fire neurons to track a finger tip or to infer directions of hand swipe motions. The experimental results show that the proposed technique can achieve graphic UI capable finger tip tracking with milliseconds intervals and accurate hand swipe motion detection with negligible latency.

Dynamic aggregation algorithms for forwarding information in distributed router architecture

As the Internet grows in size and bandwidth, packet-forwarding at the line card of routers became a technical challenge to overcome in the design of router architecture. One approach is to decrease the size of forwarding tables at line cards to reduce the time for table lookup and management. In this paper, we propose the novel algorithms that reduce the forwarding table size and the number of control packets for updating the forwarding table in a distributed router architecture. The algorithms build an aggregation tree, which aggregates the forwarding addresses dynamically. The dynamic insertion of a virtual node makes it possible to aggregate the forwarding address. The algorithms have been tested with more than 53000 BGP entries, which have been originated on a typical IPv4 BGP backbone router. We achieved 15 to 20 percent reduction in forwarding table size and number of control packets.

A routing coordination protocol in a loosely-coupled massively parallel router

In this paper, we present an efficient routing coordination based protocol which makes use of a scalable high-performance router based upon a cluster of autonomous routers to handle the routing problems raised by the current Internet growth. We also discuss a novel proprietary protocol, which we refer to as Galaxy/spl trade/ Loosely-coupled Unified Environment (or GLUE). This protocol is based upon the idea of the open shortest path first (OSPF) routing protocol. It helps the autonomous routers to maintain a consistent routing table, and monitors the status of each router using an efficient message exchange mechanism.

Limited Combining Strategies for Large-Scale Shared-Memory Multiprocessors

In a large-scale shared-memory multiprocessor, there is a possibility of serious contention due to many requests issued concurrently for the same memory location. A multistage combining network, in which each switch is enhanced with combining so that multiple requests directed to the same memory location can form a single request, significantly reduces the amount of the contention. However, employing combining in every switch of a multistage interconnection network tends to increase the cost and to slow down the network. In this paper, assuming a single-job environment, we investigate some simple strategies that allow only a limited portion of a network to have a combining capability. We show that for situations with a limited number of hot spot locations, these simple strategies can provide performance comparable to a complete combining network in which every switch is enhanced with combining