Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
We present here a new descriptor for depth images adapted to 2D/3D model matching and retrieving. We propose a representation of a 3D model by 20 depth images rendered from the ve...
Image retrieval has been widely used in many fields of science and engineering. The semantic concept of user interest is obtained by a learning process. Traditional techniques oft...
A novel algorithm is proposed to learn pattern similarities for texture image retrieval. Similar patterns in di erent texture classes are grouped into a cluster in the feature spac...
In this paper, several effective learning algorithms using global image representations are adjusted and introduced to region-based image retrieval (RBIR). First, the query point m...
Feng Jing, Mingjing Li, Lei Zhang, HongJiang Zhang...