Abstract: A distance detection method, a distance detection system and a computer program product are provided. The method includes: comparing a street view image with a real-time image according to a first distance; determining a distance between a vehicle and a target position in response to the comparison result of the street view image and the real-time image; and outputting the distance between the vehicle and the target position to prompt a user of the vehicle.

Abstract: A distance detection method, a distance detection system and a computer program product are provided. The method includes: comparing a street view image with a real-time image according to a first distance; determining a distance between a vehicle and a target position in response to the comparison result of the street view image and the real-time image; and outputting the distance between the vehicle and the target position to prompt a user of the vehicle.

Abstract: An eye detection method for detecting a degree of eye opening and closure of a testee includes detecting a location of an eye pupil, a location of an inner eye corner and a location of an outer eye corner of an eye of the testee; calculating an eye width according to the location of the inner eye corner and the location of the outer eye corner; multiplying the eye width by a specific ratio to obtain an eye height; generating a region of interest with a center on the location of the eye pupil, a length equal to the eye width, and a width equal to the eye height; and determining a ratio of the eye occupying a detection area in the region of interest, and determining the degree of eye opening and closure of the testee accordingly.

Abstract: An eye detection method for detecting a degree of eye opening and closure of a testee includes detecting a location of an eye pupil, a location of an inner eye corner and a location of an outer eye corner of an eye of the testee; calculating an eye width according to the location of the inner eye corner and the location of the outer eye corner; multiplying the eye width by a specific ratio to obtain an eye height; generating a region of interest with a center on the location of the eye pupil, a length equal to the eye width, and a width equal to the eye height; and determining a ratio of the eye occupying a detection area in the region of interest, and determining the degree of eye opening and closure of the testee accordingly.

Abstract: A gesture input system with a two-dimension (2D) image sensor and a processing module is provided. The 2D image sensor obtains a plurality of images of a user. The processing module determines positions of an object and a face of the user in a first image of the plurality of images, and determines an operation area for the user according to the positions of the object and the face. Also, the processing module generates a control command according to the subsequent images to the first image of the user within the operation area.

Abstract: An electronic device is provided, including a housing, at least one tap sensing unit and a processing unit. The housing has a touch surface, in which, when the touch surface is tapped more than one time in a predetermined interval, shock waves are generated. The tap sensing unit receives the shock waves to generate a moire signal. The processing unit obtains a shock wave source number of each of the shock waves according to the moire signal, and generates a string code according to a generation order of the shock waves and the shock wave source number of each of the shock waves, such that the processing unit controls the electronic device according to a control command corresponding to the string code.

Abstract: A gesture control method includes steps of capturing at least one image; detecting whether there is a face in the at least one image; if there is a face in the at least one image, detecting whether there is a hand in the at least one image; if there is a hand in the at least one image, identifying a gesture performed by the hand and identifying a relative distance or a relative moving speed between the hand and the face; and executing a predetermined function in a display screen according to the gesture and the relative distance or according to the gesture and the relative moving speed.

Abstract: A method for bitstream editing is provided. The method includes steps of: fetching a first original image from a source multimedia bitstream; performing variation processing on the first original image to generate a plurality of transformed pictures; performing keypoint extraction according to comparison results of the transformed pictures to obtain a plurality of candidate pixels; locating a first advertisement bitstream from an advertisement bitstream database according to the plurality of candidate pixels; and inserting the first advertisement bitstream to the source multimedia bitstream.

Abstract: A method for setting and cancelling a gesture operating region in a gesture control device includes steps of capturing at least one image; detecting whether there is a palm in the at least one image; if there is a palm in the at least one image, detecting whether there is a face in the at least one image; if there is a face in the at least one image, setting the gesture operating region according to the palm and the face; and cancelling the gesture operating region when the palm is at rest over a first time period or the palm disappears from the gesture operating region over a second time period.

Abstract: A gesture input system with a two-dimension (2D) image sensor and a processing module is provided. The 2D image sensor obtains a plurality of images of a user. The processing module determines positions of an object and a face of the user in a first image of the plurality of images, and determines an operation area for the user according to the positions of the object and the face. Also, the processing module generates a control command according to the subsequent images to the first image of the user within the operation area.

Abstract: A method for bitstream editing is provided. The method includes steps of: fetching a first original image from a source multimedia bitstream; performing variation processing on the first original image to generate a plurality of transformed pictures; performing keypoint extraction according to comparison results of the transformed pictures to obtain a plurality of candidate pixels; locating a first advertisement bitstream from an advertisement bitstream database according to the plurality of candidate pixels; and inserting the first advertisement bitstream to the source multimedia bitstream.

Abstract: An electronic device is provided, including a housing, at least one tap sensing unit and a processing unit. The housing has a touch surface, in which, when the touch surface is tapped more than one time in a predetermined interval, shock waves are generated. The tap sensing unit receives the shock waves to generate a moire signal. The processing unit obtains a shock wave source number of each of the shock waves according to the moire signal, and generates a string code according to a generation order of the shock waves and the shock wave source number of each of the shock waves, such that the processing unit controls the electronic device according to a control command corresponding to the string code.

Abstract: A gesture control method includes steps of capturing at least one image; detecting whether there is a face in the at least one image; if there is a face in the at least one image, detecting whether there is a hand in the at least one image; if there is a hand in the at least one image, identifying a gesture performed by the hand and identifying a relative distance or a relative moving speed between the hand and the face; and executing a predetermined function in a display screen according to the gesture and the relative distance or according to the gesture and the relative moving speed.

Abstract: A depth detection method includes the following steps. First, first and second video data are shot. Next, the first and second video data are compared to obtain initial similarity data including r×c×d initial similarity elements, wherein r, c and d are natural numbers greater than 1. Then, an accumulation operation is performed, with each similarity element serving as a center, according to a reference mask to obtain an iteration parameter. Next, n times of iteration update operations are performed on the initial similarity data according to the iteration parameter to generate updated similarity data. Then, it is judged whether the updated similarity data satisfy a character verification condition. If yes, the updated similarity data is converted into depth distribution data.

Abstract: A gesture detecting method includes steps of defining an initial reference point in a screen of an electronic device; dividing the screen into N areas radially according to the initial reference point; when a gesture corresponding object moves in the screen and a trajectory of the gesture corresponding object crosses M of the N areas, selecting a sample point from each of the M areas so as to obtain M sample points; and calculating a center and a radius of the trajectory of the gesture corresponding object according to P of the M sample points so as to determine a circular or curved trajectory input. Accordingly, the invention is capable of providing a center, a radius, a direction and an arc angle corresponding to a gesture in real-time without establishing a gesture model.

Abstract: A method for recognizing three-dimensional control points and a computer readable medium using the same are disclosed. The method for recognizing three-dimensional control points comprises the following steps. A depth information item corresponding to an image captured by an image capturing apparatus is received. A three-dimensional block information item corresponding to a three-dimensional block is generated according to the depth information. At least one reference plane is generated according to the depth information. At least one connection group is generated according to the three-dimensional block information and the reference plane. A three-dimensional block nearest to the image capturing apparatus is selected as a control point from the connection group.

Abstract: A system for estimating a location of an occluded skeleton, a method for estimating a location of an occluded skeleton and a method for reconstructing an occluded skeleton are provided. The method for estimating a location of an occluded skeleton comprises the following steps: Firstly, a trace of a reference central point of a body is estimated according to a plurality of continuously moving images. Next, a human movement state is estimated according to the trace and a motion information of the continuously moving images free of skeleton occlusion. Then, a possible range of the occluded skeleton for maintaining human balance is calculated according to the human movement state. Afterwards, a current motion level of the occluded skeleton is predicted according to a historic motion information of the occluded skeleton. Lastly, the location of the occluded skeleton is estimated according to the current motion level and the possible range.

Abstract: A system for estimating a location of an occluded skeleton, a method for estimating a location of an occluded skeleton and a method for reconstructing an occluded skeleton are provided. The method for estimating a location of an occluded skeleton comprises the following steps: Firstly, a trace of a reference central point of a body is estimated according to a plurality of continuously moving images. Next, a human movement state is estimated according to the trace and a motion information of the continuously moving images free of skeleton occlusion. Then, a possible range of the occluded skeleton for maintaining human balance is calculated according to the human movement state. Afterwards, a current motion level of the occluded skeleton is predicted according to a historic motion information of the occluded skeleton. Lastly, the location of the occluded skeleton is estimated according to the current motion level and the possible range.

Abstract: A method for recognizing three-dimensional control points and a computer readable medium using the same are disclosed. The method for recognizing three-dimensional control points comprises the following steps. A depth information item corresponding to an image captured by an image capturing apparatus is received. A three-dimensional block information item corresponding to a three-dimensional block is generated according to the depth information. At least one reference plane is generated according to the depth information. At least one connection group is generated according to the three-dimensional block information and the reference plane. A three-dimensional block nearest to the image capturing apparatus is selected as a control point from the connection group.

Abstract: A depth detection method includes the following steps. First, first and second video data are shot. Next, the first and second video data are compared to obtain initial similarity data including r×c×d initial similarity elements, wherein r, c and d are natural numbers greater than 1. Then, an accumulation operation is performed, with each similarity element serving as a center, according to a reference mask to obtain an iteration parameter. Next, n times of iteration update operations are performed on the initial similarity data according to the iteration parameter to generate updated similarity data. Then, it is judged whether the updated similarity data satisfy a character verification condition. If yes, the updated similarity data is converted into depth distribution data.