Amazon Technologies, Inc.

Rawles LLC

Weijian Wang

Samuel Henry Chang

Ning Yao

Edward Dietz Crump

Olusanya Temitope Soyannwo

Renwei Yan

Amit Kumar Agrawal

Qiang Liu

Rohith Mysore Vijaya Kumar

Prakash Ramu

Sowmya Gopalan

Visesh Uday Kumar Chari

Manika Puri

Yadunandana Nagaraja Rao

Abhishek Singh

Lelin Zhang

Yuhua Zhu

Devices and techniques are generally described for segmentation of image data using depth data. In various examples, color image data may be received from a digital camera. In some examples, depth image data may be received from a depth sensor. In various examples, the depth image data may be separated into a plurality of clusters of depth image data, wherein each cluster is associated with a respective range of depth values. In some further examples, a determination may be made that a first cluster of image data corresponds to an object of interest, such as a human subject, in the image data. In various examples, pixels of the first cluster may be encoded with foreground indicator data. In some further examples, segmented image data may be generated. The segmented image data may comprise pixels encoded with the foreground indicator data.

Image data segmentation using depth data

Techniques are described for performing automatic focusing of a projected image on a mobile projection surface. Specific regions of the projected image are identified that are likely to be desired to stay in optimal focus, and attributes of those specific regions, such as sharpness and contrast, can be used to determine the need to refocus the image. Advanced knowledge of the image data being projected can be utilized to determine the specific regions of the projected image that require monitoring for optimal focusing.

Automatic projection focusing

Techniques are described for projecting content onto surfaces and for focusing the content. When content is projected by a projector onto a surface, the surface is observed by a camera or other sensor, and the contrast of the projected content is evaluated. The projector then varies its focal point to improve or maximize the observed contrast of the projected content.

Projection autofocus

Techniques are described for detecting a hand gesture made by a user. Fingertips of a hand may be identified and tracked over time. When a user contracts the fingertips from an extended position, hand spread may be calculated based on the area of the hand and fingers. The hand spread over time may be compared to a Gaussian function to evaluate whether the observed motion represents a grasping motion.

Hand gesture detection

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Cupertino, CA, United States of America

Weijian Wang