A system includes a sensor component and a detection component. The sensor component (106-114) is configured to obtain first and second streams of sensor data, wherein each of the streams comprises a plurality of frames 702. The detection component 104 is configured to generate a concatenated feature map 704 based on a sensor frame of a first type (e.g. an image) and a sensor frame of a second type (e.g. a depth map). The detection component is also configured to detect one or more objects 706 based on the concatenated feature map. The generating and/or detecting comprises using a neural network (NN, 200) with a recurrent connection that feeds forward information about features or objects from previous frames. For example, output from the classification layer of the NN for an earlier frame could be fed into an input layer (202) or hidden layer (204-208) for a later frame. The invention could be applied to autonomous vehicles or driver assistance systems, for example to detect obstacles such as pedestrians (302).
Object detection using recurrent neural network and concatenated feature map