Abstract: Techniques for calibrating a device having a stereoscopic camera are disclosed. According to an embodiment, the device calibrates the stereoscopic camera using a target provided by a mobile device. One or more zones each defining an area in a field of view of the calibrated stereoscopic camera are generated. The one or more zones are refined based on input provided by the mobile device.

Abstract: Techniques for distinguishing objects (e.g., an individual or an individual pushing a shopping cart) are disclosed. An object is detected in images of a scene. A height map is generated from the images, and the object is represented as height values in the height map. Based on height properties associated with another object, it is determined whether the other object is associated with the object. If so determined, the objects are classified separately.

Abstract: A method of identifying, tracking, and counting human objects of interest based upon at least one pair of stereo image frames taken by at least one image capturing device, comprising the steps of: obtaining said stereo image frames and converting each said stereo image frame to a rectified image frame using calibration data obtained for said at least one image capturing device; generating a disparity map based upon a pair of said rectified image frames; generating a depth map based upon said disparity map and said calibration data; identifying the presence or absence of said objects of interest from said depth map and comparing each of said objects of interest to existing tracks comprising previously identified objects of interest; for each said presence of an object of interest, adding said object of interest to one of said existing tracks if said object of interest matches said one existing track, or creating a new track comprising said object of interest if said object of interest does not match any of sai

Abstract: Techniques for distinguishing objects (e.g., an individual or an individual pushing a shopping cart) are disclosed. An object is detected in images of a scene. A height map is generated from the images, and the object is represented as height values in the height map. Based on height properties associated with another object, it is determined whether the other object is associated with the object. If so determined, the objects are classified separately.

Abstract: A testing device for study of a magnetized plasma artillery and gunpowder, comprising a pedestal, wherein a top end of the pedestal is provided with a sliding slot for mounting a buffer device, which penetrates through an upper part of the pedestal along a front-rear direction. The sliding slot for mounting the buffer device is internally provided with a buffering slider, which can slide back and forth along the sliding slot for mounting the buffer device. A top end of the buffering slider is provided with a gunpowder combustion chamber fixing groove, which penetrates through an upper part of the buffering slider along the front-rear direction. The gunpowder combustion chamber fixing groove is internally provided with a gunpowder combustion chamber, and an upper part of the gunpowder combustion chamber is provided with a positioning ferrule for fixing the gunpowder combustion chamber.

Abstract: Techniques for distinguishing objects (e.g., an individual or an individual pushing a shopping cart) are disclosed. An object is detected in images of a scene. A height map is generated from the images, and the object is represented as height values in the height map. Based on height properties associated with another object, it is determined whether the other object is associated with the object. If so determined, the objects are classified separately.

Abstract: A system is disclosed that includes: at least one image capturing device at the entrance to obtain images; a reader device; and a processor for extracting objects of interest from the images and generating tracks for each object of interest, and for matching objects of interest with objects associated with RFID tags, and for counting the number of objects of interest associated with, and not associated with, particular RFID tags.

Abstract: A method for recognizing a voice and a device for recognizing a voice are provided. The method includes: collecting voice information input by a user; extracting characteristics from the voice information to obtain characteristic information; decoding the characteristic information according to an acoustic model and a language model obtained in advance to obtain recognized voice information, wherein the acoustic model is obtained by data compression in advance.

Abstract: A method for recognizing a voice and a device for recognizing a voice are provided. The method includes: collecting voice information input by a user; extracting characteristics from the voice information to obtain characteristic information; decoding the characteristic information according to an acoustic model and a language model obtained in advance to obtain recognized voice information, wherein the acoustic model is obtained by data compression in advance.

Abstract: A method of identifying, tracking, and counting human objects of interest based upon at least one pair of stereo image frames taken by at least one image capturing device, comprising the steps of: obtaining said stereo image frames and converting each said stereo image frame to a rectified image frame using calibration data obtained for said at least one image capturing device; generating a disparity map based upon a pair of said rectified image frames; generating a depth map based upon said disparity map and said calibration data; identifying the presence or absence of said objects of interest from said depth map and comparing each of said objects of interest to existing tracks comprising previously identified objects of interest; for each said presence of an object of interest, adding said object of interest to one of said existing tracks if said object of interest matches said one existing track, or creating a new track comprising said object of interest if said object of interest does not match any of sai

Abstract: A method of identifying, tracking, and counting human objects of interest based upon at least one pair of stereo image frames taken by at least one image capturing device, comprising the steps of: obtaining said stereo image frames and converting each said stereo image frame to a rectified image frame using calibration data obtained for said at least one image capturing device; generating a disparity map based upon a pair of said rectified image frames; generating a depth map based upon said disparity map and said calibration data; identifying the presence or absence of said objects of interest from said depth map and comparing each of said objects of interest to existing tracks comprising previously identified objects of interest; for each said presence of an object of interest, adding said object of interest to one of said existing tracks if said object of interest matches said one existing track, or creating a new track comprising said object of interest if said object of interest does not match any of sai

Abstract: A system is disclosed that includes: at least one image capturing device at the entrance to obtain images; a reader device; and a processor for extracting objects of interest from the images and generating tracks for each object of interest, and for matching objects of interest with objects associated with RFID tags, and for counting the number of objects of interest associated with, and not associated with, particular RFID tags.

Abstract: This invention presents the development of flexible battery especially primary and secondary alkaline batteries. Nano carbons, in particularly carbon nanotubes are implemented in conductive polymers to develop flexible electrodes. Polymer separators that can withstand high pH and serve the purpose of electrolyte storage is used to enhance performance. The relatively inexpensive multiwall nanotubes represent are effective ingredients in development of flexible electrodes.

Abstract: A system is disclosed that includes: at least one image capturing device at the entrance to obtain images; a reader device; and a processor for extracting objects of interest from the images and generating tracks for each object of interest, and for matching objects of interest with objects associated with RFID tags, and for counting the number of objects of interest associated with, and not associated with, particular RFID tags.

Abstract: A method of identifying, tracking, and counting human objects of interest based upon at least one pair of stereo image frames taken by at least one image capturing device, comprising the steps of: obtaining said stereo image frames and converting each said stereo image frame to a rectified image frame using calibration data obtained for said at least one image capturing device; generating a disparity map based upon a pair of said rectified image frames; generating a depth map based upon said disparity map and said calibration data; identifying the presence or absence of said objects of interest from said depth map and comparing each of said objects of interest to existing tracks comprising previously identified objects of interest; for each said presence of an object of interest, adding said object of interest to one of said existing tracks if said object of interest matches said one existing track, or creating a new track comprising said object of interest if said object of interest does not match any of sai

Abstract: A method of identifying, tracking, and counting human objects of interest based upon at least one pair of stereo image frames taken by at least one image capturing device, comprising the steps of: obtaining said stereo image frames and converting each said stereo image frame to a rectified image frame using calibration data obtained for said at least one image capturing device; generating a disparity map based upon a pair of said rectified image frames; generating a depth map based upon said disparity map and said calibration data; identifying the presence or absence of said objects of interest from said depth map and comparing each of said objects of interest to existing tracks comprising previously identified objects of interest; for each said presence of an object of interest, adding said object of interest to one of said existing tracks if said object of interest matches said one existing track, or creating a new track comprising said object of interest if said object of interest does not match any of sai

Abstract: A method of identifying, tracking, and counting objects of interest based upon at least one pair of stereo image frames taken by at least one image capturing device comprises the steps of: obtaining said at least one pair of stereo image frames and converting each said stereo image frame to a rectified image frame using calibration data obtained from said at least one image capturing device; identifying the presence or absence of said objects of interest and comparing each of said objects of interest to existing tracks comprising previously identified objects of interest; and for each said presence of an object of interest, adding said object of interest to one of said existing tracks if said object of interest matches said one existing track, or creating a new track comprising said object of interest if said object of interest does not match any of said existing tracks.

Abstract: A method of identifying, tracking, and counting human objects of interest based upon at least one pair of stereo image frames taken by at least one image capturing device, comprising the steps of: obtaining said stereo image frames and converting each said stereo image frame to a rectified image frame using calibration data obtained for said at least one image capturing device; generating a disparity map based upon a pair of said rectified image frames; generating a depth map based upon said disparity map and said calibration data; identifying the presence or absence of said objects of interest from said depth map and comparing each of said objects of interest to existing tracks comprising previously identified objects of interest; for each said presence of an object of interest, adding said object of interest to one of said existing tracks if said object of interest matches said one existing track, or creating a new track comprising said object of interest if said object of interest does not match any of sai

Abstract: A method of identifying, tracking, and counting human objects of interest based upon at least one pair of stereo image frames taken by at least one image capturing device, comprising the steps of: obtaining said stereo image frames and converting each said stereo image frame to a rectified image frame using calibration data obtained for said at least one image capturing device; generating a disparity map based upon a pair of said rectified image frames; generating a depth map based upon said disparity map and said calibration data; identifying the presence or absence of said objects of interest from said depth map and comparing each of said objects of interest to existing tracks comprising previously identified objects of interest; for each said presence of an object of interest, adding said object of interest to one of said existing tracks if said object of interest matches said one existing track, or creating a new track comprising said object of interest if said object of interest does not match any of sai

Abstract: A system is disclosed that includes: at least one image capturing device at the entrance to obtain images; a reader device; and a processor for extracting objects of interest from the images and generating tracks for each object of interest, and for matching objects of interest with objects associated with RFID tags, and for counting the number of objects of interest associated with, and not associated with, particular RFID tags.