Abstract: Non-encoded data for a macroblock of an image frame is accessed. A cost to intra-encode the macroblock is computed using at least a portion of the non-encoded data in place of reconstructed image data from another macroblock of the image frame. The cost can be compared against the cost to inter-encode the first macroblock in order to select how the first macroblock is to be encoded.

Abstract: A manual human machine interface operation system and method thereof are disclosed. In embodiment, this manual human machine interface operation system extracts user's arm image and palm image from the images capture by at least two cameras, and then calculates user's arm coordinate, so that user can select the object shown on the human machine interface by manually using his/her arm. The system then recognizes a hand posture according to the palm image and determines an instruction mapped to this hand posture. This instruction is then performed on the selected object. In embodiment, the hand posture can be a pointing posture, grab posture or a release posture.

Abstract: An image based motion gesture recognition method and system thereof are disclosed. In embodiment, a hand posture detection is performed according to the received image frames, to obtain a first hand posture. It is then determined whether the first hand posture matches a predefined starting posture or not. If the first hand posture matches said predefined starting posture, movement tracking is performed according to hand locations on image frames, to obtain a motion gesture. During said movement tracking, the hand posture detection is performed according to said image frames to obtain a second hand posture, and it is determined whether the second hand posture matches a predefined ending posture. If the second hand posture matches the predefined ending posture, the movement tracking is stopped. Therefore, reduce complexity motion gesture recognition can be reduced and the reliability in interaction can be improved.

Abstract: A vision-based hand movement recognition system and method thereof are disclosed. In embodiment, a hand posture is recognized according to consecutive hand images first. If the hand posture matches a start posture, the system then separates the consecutive hand images into multiple image groups and calculates motion vectors of these image groups. The distributions of these motion vectors are compared with multiple three-dimensional motion vector histogram equalizations to determine a corresponding movement for each image group. For example, the corresponding movement can be a left moving action, a right moving action, an up moving action or a down moving action. Finally, the combination of these corresponding movements is defined as a gesture, and an instruction mapped to this gesture is then executed.

Abstract: A manual human machine interface operation system and method thereof are disclosed. In embodiment, this manual human machine interface operation system extracts user's arm image and palm image from the images capture by at least two cameras, and then calculates user's arm coordinate, so that user can select the object shown on the human machine interface by manually using his/her arm. The system then recognizes a hand posture according to the palm image and determines an instruction mapped to this hand posture. This instruction is then performed on the selected object. In embodiment, the hand posture can be a pointing posture, grab posture or a release posture.

Abstract: A vision based hand posture recognition method and system thereof are disclosed. The method comprises the following steps of receiving an image frame; extracting a contoured hand image from said image frame; calculating a gravity center of said contoured hand image; obtaining contour points on a contour of said contoured hand image; calculating distances between said gravity center and said multiple contour points; recognizing a hand posture according to a first characteristic function of said multiple contour points. In embodiment, the finger number and hand direction of the hand posture can be determined according to the number and location of at least one peak of the first characteristic function.

Abstract: An image based motion gesture recognition method and system thereof are disclosed. In embodiment, a hand posture detection is performed according to the received image frames, to obtain a first hand posture. It is then determined whether the first hand posture matches a predefined starting posture or not. If the first hand posture matches said predefined starting posture, movement tracking is performed according to hand locations on image frames, to obtain a motion gesture. During said movement tracking, the hand posture detection is performed according to said image frames to obtain a second hand posture, and it is determined whether the second hand posture matches a predefined ending posture. If the second hand posture matches the predefined ending posture, the movement tracking is stopped. Therefore, reduce complexity motion gesture recognition can be reduced and the reliability in interaction can be improved.

Abstract: Non-encoded data for a macroblock of an image frame is accessed. A cost to intra-encode the macroblock is computed using at least a portion of the non-encoded data in place of reconstructed image data from another macroblock of the image frame. The cost can be compared against the cost to inter-encode the first macroblock in order to select how the first macroblock is to be encoded.