Industrial Technology Research Institute

Hsin-Cheng Lin

Sen-Yih Chou

Chia-Liang Yeh

Yu-Ying Lan

Chih-Chia Chang

Yu-Hsin Lin

Chung-Lun Kuo

Ting-Hsun Cheng

Hsin-Yi Chen

Yu-Ju Chao

Hsiao-Wei Liu

An image recognition method, a training system for an object recognition model and a training method for an object recognition model are provided. The image recognition method includes the following steps. At least one original sample image of an object in a field and an object range information and an object type information in the original sample image are obtained. At least one physical parameter is adjusted to generate plural simulated sample images of the object. The object range information and the object type information of the object in each of the simulated sample images are automatically marked. A machine learning procedure is performed to train an object recognition model. An image recognition procedure is performed on an input image.

Image recognition method, training system for object recognition model and training method for object recognition model

A recognition system and an image augmentation and training method thereof are provided. The image augmentation and training method of a recognition system includes the following steps. A plurality of image frames are obtained, wherein each of the image frames includes an object pattern. A plurality of environmental patterns are obtained. The object pattern is separated from each of the image frames. A plurality of image parameters are set. The image frames, based on the object patterns and the environmental patterns, are augmented according to the image parameters to increase the number of the image frames. A recognition model is trained using the image frames.

Recognition system and image augmentation and training method thereof

An object identification method includes: establishing a training data base including a photographing distance of a training image and a training camera parameter; in photographing a target test object, obtaining a test image, a depth image, an RGB image and a test camera parameter; and based on the training database, the depth image and the test camera parameter, adjusting the RGB image wherein the adjusted RGB image having a size equivalent to the training image of the training database.

Object identification method and device

A sight vector detecting method includes: capturing a user image by an image capture unit and a depth capture unit to obtain a first image and a distance information; based on the first image and the distance information, finding an eye center location of the user; predicting a user sight location by a gaze model to find a target sight location of the user on a target; based on the eye center location of the user, finding a first word coordinate of the eye center location of the user; based on the target sight location of the user, finding a second word coordinate of the target sight location of the user; and based on the first word coordinate of the eye center location of the user and the second word coordinate of the target sight location of the user, calculating a sight vector of the user.

Sight vector detecting method and device

An eye tracking apparatus and an eye tracking method for the eye tracking apparatus are provided. The eye tracking apparatus includes an image capture device and a computing device. The image capture device is adapted to capture at least one face image. The computing device is coupled to the image capture device. The computing device receives the face image to obtain an eye image and identifies at least one iris region of the eye image. The computing device chooses the largest iris region from the iris regions to obtain a fitting pattern of the largest iris region and obtains a gaze point of the eye image based on the fitting pattern.

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Hemei, Taiwan

Hsin-Cheng Lin