Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
Computer vision researchers have recently proposed several local descriptor schemes. Due to lack of database support, however, these descriptors have only been evaluated using sma...
This paper's intention is to adapt prediction algorithms well known in the field of time series analysis to problems being faced in the field of mobile robotics and Human-Robo...
Abstract. We present a refined method for rotation estimation of signals on the 2-Sphere. Our approach utilizes a fast correlation in the harmonic domain to estimate rotation angle...
Abstract. Due to stringing time constraints, saliency models are becoming popular tools for building situated robotic systems requiring, for instance, object recognition and vision...