Abstract: A computer-implemented method of generating a spatio-temporal pattern model for spatio-temporal pattern recognition includes receiving one or more training trajectories. Each of the training trajectories includes diverse data points that represent a spatio-temporal pattern. The received training trajectories define an area that is partitioned into one or more observed clusters, and a unpopulated complementary cluster. The spatio-temporal pattern model is generated so as to include both of the observed clusters and the unpopulated complementary cluster.

Abstract: Various arrangements for recognizing gestures are presented. A plurality of color images of a scene may be received. Each image of the plurality of color images may be processed to make a plurality of processed color images. The processing of an image of the plurality of color images may comprise grouping pixels of the image being processed into a plurality of clusters based on color. A gesture may be identified using movement of a cluster of the plurality of clusters in the plurality of processed color images.

Abstract: Techniques are provided to improve interaction between a user and a projection system. In some embodiments, an image of a user in front of a display screen is captured. An inference can then be made as to whether a user is touching a display screen based on an analysis of shadows and/or variation of brightness (i.e., intensities) across pixels in the image. For example, it may be inferred that the object is: (1) approaching the screen when a region surrounding a top of the object is characterized by a relatively small brightness variation; (2) hovering near the screen when the brightness variation is large and the region includes a dark extremum (caused by a shadow); and (3) touching the screen when the brightness variation is large and the region includes a light extremum.

Abstract: A computer-implemented method of generating a spatio-temporal pattern model for spatio-temporal pattern recognition includes receiving one or more training trajectories. Each of the training trajectories includes diverse data points that represent a spatio-temporal pattern. The received training trajectories define an area that is partitioned into one or more observed clusters, and a non-observed complementary cluster. The spatio-temporal pattern model is generated so as to include both of the observed clusters and the non-observed complementary cluster.

Abstract: Motion of a device is sensed using image data, and a gesture corresponding to the sensed motion of the device is recognized. Functionality of the device corresponding to the recognized gesture is determined and invoked.

Abstract: Techniques are provided to improve interaction between a user and a projection system. In some embodiments, an image of a user in front of a display screen is captured. An inference can then be made as to whether a user is touching a display screen based on an analysis of shadows and/or variation of brightness (i.e., intensities) across pixels in the image. For example, it may be inferred that the object is: (1) approaching the screen when a region surrounding a top of the object is characterized by a relatively small brightness variation; (2) hovering near the screen when the brightness variation is large and the region includes a dark extremum (caused by a shadow); and (3) touching the screen when the brightness variation is large and the region includes a light extremum.

Abstract: Techniques are provided to improve interaction between a user and a projection system. In some embodiments, an image of a user in front of a display screen is captured. An inference can then be made as to whether a user is touching a display screen based on an analysis of shadows and/or variation of brightness (i.e., intensities) across pixels in the image. For example, it may be inferred that the object is: (1) approaching the screen when a region surrounding a top of the object is characterized by a relatively small brightness variation; (2) hovering near the screen when the brightness variation is large and the region includes a dark extremum (caused by a shadow); and (3) touching the screen when the brightness variation is large and the region includes a light extremum.

Abstract: Enhanced input using flashing electromagnetic radiation, in which first and second images of an object are accessed. The first image being captured while the object is illuminated with projected electromagnetic radiation, and the second image being captured while the projected electromagnetic radiation is extinguished. A position of the object relative to the screen based on comparing the first and second images is determined. An application is controlled based on the determined position.

Abstract: Various arrangements for recognizing gestures are presented. A plurality of color images of a scene may be received. Each image of the plurality of color images may be processed to make a plurality of processed color images. The processing of an image of the plurality of color images may comprise grouping pixels of the image being processed into a plurality of clusters based on color. A gesture may be identified using movement of a cluster of the plurality of clusters in the plurality of processed color images.

Abstract: Enhanced rejection of out-of-vocabulary words, in which, based on applying an input gesture to hidden Markov models collectively modeling a vocabulary of training gestures, a likelihood that the input gesture matches each training gesture, and a quantity of states of the input gesture that match corresponding states of a modeled training gesture determined to have a highest likelihood are determined. The input gesture is rejected if the determined quantity does not satisfy a threshold.

Abstract: Enhanced input using flashing electromagnetic radiation, in which first and second images of an object are accessed. The first image being captured while the object is illuminated with projected electromagnetic radiation, and the second image being captured while the projected electromagnetic radiation is extinguished. A position of the object relative to the screen based on comparing the first and second images is determined. An application is controlled based on the determined position.

Abstract: Hands may be tracked before, during, and after occlusion, and a gesture may be recognized. Movement of two occluded hands may be tracked as a unit during an occlusion period. A type of synchronization characterizing the two occluded hands during the occlusion period may be determined based on the tracked movement of the occluded hands. Based on the determined type of synchronization, it may be determined whether directions of travel for each of the two occluded hands change during the occlusion period. Implementations may determine that a first hand and a second hand are occluded during an occlusion period, the first hand having come from a first direction and the second hand having come from a second direction. The first hand may be distinguished from the second hand after the occlusion period based on a determined type of synchronization characterizing the two hands, and a behavior of the two hands.

Abstract: According to one disclosed method, coordinates in a multi-dimensional space are determined for an image point characterizing a particular object. An equation describing a model in the space is provided. The model is characteristic of a set of training images of one or more other objects. The coordinates are applied to the equation to determine a distance between the image point and the model. Based on the determined distance, a determination is made as to whether the particular object matches the one or more other objects. A set of training images may be received. A multi-dimensional space (e.g., eigenspace) may be determined based on the set of training images. A set of training points may be generated by projecting the set of training images into the multi-dimensional space. An equation describing a model in the multi-dimensional space that is characteristic of the set of training points may be determined.

Abstract: Enhanced input using flashing electromagnetic radiation, in which first and second images of an object are accessed. The first image being captured while the object is illuminated with projected electromagnetic radiation, and the second image being captured while the projected electromagnetic radiation is extinguished. A position of the object relative to the screen based on comparing the first and second images is determined. An application is controlled based on the determined position.

Abstract: Hands may be tracked before, during, and after occlusion, and a gesture may be recognized. Movement of two occluded hands may be tracked as a unit during an occlusion period. A type of synchronization characterizing the two occluded hands during the occlusion period may be determined based on the tracked movement of the occluded hands. Based on the determined type of synchronization, it may be determined whether directions of travel for each of the two occluded hands change during the occlusion period. Implementations may determine that a first hand and a second hand are occluded during an occlusion period, the first hand having come from a first direction and the second hand having come from a second direction. The first hand may be distinguished from the second hand after the occlusion period based on a determined type of synchronization characterizing the two hands, and a behavior of the two hands.

Abstract: Hands may be tracked before, during, and after occlusion, and a gesture may be recognized. Movement of two occluded hands may be tracked as a unit during an occlusion period. A type of synchronization characterizing the two occluded hands during the occlusion period may be determined based on the tracked movement of the occluded hands. Based on the determined type of synchronization, it may be determined whether directions of travel for each of the two occluded hands change during the occlusion period. Implementations may determine that a first hand and a second hand are occluded during an occlusion period, the first hand having come from a first direction and the second hand having come from a second direction. The first hand may be distinguished from the second hand after the occlusion period based on a determined type of synchronization characterizing the two hands, and a behavior of the two hands.

Abstract: According to one disclosed method, coordinates in a multi-dimensional space are determined for an image point characterizing a particular object. An equation describing a model in the space is provided. The model is characteristic of a set of training images of one or more other objects. The coordinates are applied to the equation to determine a distance between the image point and the model. Based on the determined distance, a determination is made as to whether the particular object matches the one or more other objects. A set of training images may be received. A multi-dimensional space (e.g., eigenspace) may be determined based on the set of training images. A set of training points may be generated by projecting the set of training images into the multi-dimensional space. An equation describing a model in the multi-dimensional space that is characteristic of the set of training points may be determined.

Abstract: Enhanced input using flashing electromagnetic radiation, in which first and second images of an object are accessed. The first image being captured while the object is illuminated with projected electromagnetic radiation, and the second image being captured while the projected electromagnetic radiation is extinguished. A position of the object relative to the screen based on comparing the first and second images is determined. An application is controlled based on the determined position.

Abstract: According to one disclosed method, coordinates in a multi-dimensional space are determined for an image point characterizing a particular object. An equation describing a model in the space is provided. The model is characteristic of a set of training images of one or more other objects. The coordinates are applied to the equation to determine a distance between the image point and the model. Based on the determined distance, a determination is made as to whether the particular object matches the one or more other objects. A set of training images may be received. A multi-dimensional space (e.g., eigenspace) may be determined based on the set of training images. A set of training points may be generated by projecting the set of training images into the multi-dimensional space. An equation describing a model in the multi-dimensional space that is characteristic of the set of training points may be determined.

Abstract: Enhanced input using flashing electromagnetic radiation, in which first and second images, captured on a first side of a screen, of an object and an ambient electromagnetic radiation emitter disposed on a second side of the screen, are accessed. The first image being captured while the object is illuminated with projected electromagnetic radiation, and the second image being captured while the projected electromagnetic radiation is extinguished. A position of the object relative to the screen based on comparing the first and second images is determined. An application is controlled based on the determined position.