Industrial Technology Research Institute

Cheng-Feng Wu

Wen-Chao Chen

Kai-Che Liu

Qi Wu

Cheng-Yuan Tang

Shih-Pin Chao

Fu-Chiang Jan

Te-Chin Shao

Tsu-Han Chen

Image classification methods and systems are provided. First, an image is obtained using a computer. The image is then processed using the computer to obtain image information. The image information includes one or any combination of an average color difference between at least one average channel value of pixels in at least one boundary region of the image and a predefined standard value, a gradient variation magnitude difference between at least two regions of the image, and a percentage of the edges of the image to the image. The image is classified using the computer according to the image information.

Image classification methods and systems

Gesture recognition methods and systems are provided. First, a plurality of gesture templates are provided, wherein each gesture template defines a first gesture characteristic and a corresponding specific gesture. Then, a plurality of images is obtained, and a multi-background model is generated accordingly. At least one object image is obtained according to the multi-background model, wherein the object image includes at least an object having a plurality of edges. The included angles of any two adjacent edges of the object image are gathered as statistics to obtain a second gesture characteristic corresponding to the object image. The second gesture characteristic of the object image is compared with the first gesture characteristic of each gesture template. The specific gesture corresponding to the first gesture characteristic is obtained, when the second gesture characteristic is similar to the first gesture characteristic.

Gesture recognition methods and systems

An example-based 2D to 3D image conversion method, a computer readable medium therefore, and a system are provided. The embodiments are based on an image database with depth information or with which depth information can be generated. With respect to a 2D image to be converted into 3D content, a matched background image is found from the database. In addition, graph-based segmentation and comparison techniques are employed to detect the foreground of the 2D image so that the relative depth map can be generated from the foreground and background information. Therefore, the 3D content can be provided with the 2D image plus the depth information. Thus, users can rapidly obtain the 3D content from the 2D image automatically and the rendering of the 3D content can be achieved.

Example-based two-dimensional to three-dimensional image conversion method, computer readable medium therefor, and system

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Chiayi County, Taiwan

Cheng-Feng Wu