Abstract: An intelligent video editing method including: receiving and decoding an image data stream from a source storage device to generate an image sequence; performing image extraction operations on the image sequence at intervals of a predetermined time to obtain a plurality of image shots; selecting a frame out of each aforementioned image shot as a candidate frame, and performing a comparison operation on any two consecutive aforementioned candidate frames to derive a group of aforementioned candidate frames belonging to a same scene, and selecting one aforementioned candidate frame from the group as a target frame; and performing an AI evaluation operation on each aforementioned target frame to classify and/or rate each aforementioned target frame.

Abstract: An intelligent video editing method including: receiving and decoding an image data stream from a source storage device to generate an image sequence; performing image extraction operations on the image sequence at intervals of a predetermined time to obtain a plurality of image shots; selecting a frame out of each aforementioned image shot as a candidate frame, and performing a comparison operation on any two consecutive aforementioned candidate frames to derive a group of aforementioned candidate frames belonging to a same scene, and selecting one aforementioned candidate frame from the group as a target frame; and performing an AI evaluation operation on each aforementioned target frame to classify and/or rate each aforementioned target frame.

Abstract: A recycling system and a method based on deep-learning and computer vision technology are disclosed. The system includes a trash sorting device and a trash sorting algorithm. The trash sorting device includes a trash arraying mechanism, trash sensors, a trash transfer mechanism and a controller. The trash arraying mechanism is configured to process trash in a batch manner. The controller drives the trash arraying mechanism according to the signals of trash sensors and controls the sorting gates of the trash sorting mechanism to rotate. The trash sorting algorithm makes use of the images of trash, wherein the images are taken by cameras in different directions. The trash sorting algorithm includes a dynamic object detection algorithm, an image pre-processing algorithm, an identification module and a voting and selecting algorithm. The identification module is based on the convolutional neural networks (CNNs) and may at least identify four kinds of trash.

Abstract: A recycling system and a method based on deep-learning and computer vision technology are disclosed. The system includes a trash sorting device and a trash sorting algorithm. The trash sorting device includes a trash arraying mechanism, trash sensors, a trash transfer mechanism and a controller. The trash arraying mechanism is configured to process trash in a batch manner. The controller drives the trash arraying mechanism according to the signals of trash sensors and controls the sorting gates of the trash sorting mechanism to rotate. The trash sorting algorithm makes use of the images of trash, wherein the images are taken by cameras in different directions. The trash sorting algorithm includes a dynamic object detection algorithm, an image pre-processing algorithm, an identification module and a voting and selecting algorithm. The identification module is based on the convolutional neural networks (CNNs) and may at least identify four kinds of trash.

Abstract: A head mounted display apparatus and a calibrating method thereof are provided. The HMD apparatus has a dual camera unit. The method includes: disposing a reference object in front of the dual camera unit, wherein the reference object has at least one physical feature; capturing a plurality of images of the reference object by the dual camera unit, and generating a distance information of the reference object according to the images; determining whether the dual camera unit being deformed or not by analyzing the distance information; and calibrating the HMD apparatus if the dual camera unit being deformed.

Abstract: A virtual reality system is provided. The virtual reality system includes a host device, a transmission cable, and a head mounted display apparatus worn by a user and coupled to the host device via the transmission cable. The head mounted display apparatus includes a multimedia module, a multi-sensing module, and a peripheral hub. The multimedia module receives multimedia content from the host device via the transmission cable, and displays a video part of the multimedia content. The multi-sensing module obtains sensing information regarding the head mounted display apparatus, the user and an obstruction. The peripheral hub provides the sensing information to the host device via the transmission cable. At least one virtual object of the video part of the multimedia content is adjusted in response to the sensing information.

Abstract: An electronic device and a focus adjustment method thereof are provided. The electronic device and the focus adjustment method thereof pre-process the image frames captured to provide focus information of the image frames and adjust the focus according to the focus information. Therefore, as the subject followed or the current scene is out of focus in response to movement of the electronic device, the present invention can immediately obtain the change of focus via the focus information and effectively adjust the focus according to the focus information.

Abstract: A head mounted display apparatus and a calibrating method thereof are provided. The HMD apparatus has a dual camera unit. The method includes: disposing a reference object in front of the dual camera unit, wherein the reference object has at least one physical feature; capturing a plurality of images of the reference object by the dual camera unit, and generating a distance information of the reference object according to the images; determining whether the dual camera unit being deformed or not by analyzing the distance information; and calibrating the HMD apparatus if the dual camera unit being deformed.

Abstract: A virtual reality system is provided. The virtual reality system includes a host device, a transmission cable, and a head mounted display apparatus worn by a user and coupled to the host device via the transmission cable. The head mounted display apparatus includes a multimedia module, a multi-sensing module, and a peripheral hub. The multimedia module receives multimedia content from the host device via the transmission cable, and displays a video part of the multimedia content. The multi-sensing module obtains sensing information regarding the head mounted display apparatus, the user and an obstruction. The peripheral hub provides the sensing information to the host device via the transmission cable. At least one virtual object of the video part of the multimedia content is adjusted in response to the sensing information.

Abstract: An electronic device and a focus adjustment method thereof are provided. The electronic device and the focus adjustment method thereof pre-process the image frames captured to provide focus information of the image frames and adjust the focus according to the focus information. Therefore, as the subject followed or the current scene is out of focus in response to movement of the electronic device, the present invention can immediately obtain the change of focus via the focus information and effectively adjust the focus according to the focus information.