Towards an Efficient Distributed Object Recognition System in Wireless Smart Camera Networks
Source: University of California
The authors propose an efficient distributed object recognition system for sensing, compression, and recognition of 3-D objects and landmarks using a network of wireless smart cameras. The foundation is based on a recent work that shows the representation of scale-invariant image features exhibit certain degree of sparsity: if a common object is observed by multiple cameras from different vantage points, the corresponding features can be efficiently compressed in a distributed fashion, and the joint signals can be simultaneously decoded based on distributed compressive sensing theory. In this paper, they first present a public multiple-view object recognition database, called the Berkeley Multi-view Wireless (BMW) database.