JAR-AIBO: A multi-view dataset for evaluation of model-free action recognition systems

Abstract

Abstract. We present a novel multi-view dataset for evaluating model-free action recognition systems. Superior to existing datasets, it covers 56 distinct action classes. Each of them was performed ten times by remotely controlled Sony ERS-7 AIBO robot dogs observed by six distributed and synchronized cameras at 17 fps and VGA resolution. In total, our dataset contains 576 sequences. Baseline results show its applicability for benchmarking model-free action recognition methods