Abstract:
Systems and methods are disclosed for detecting light sources and selectively adjusting exposure times of individual sensors in image sensors. In one aspect, a method includes capturing multiple images of a scene using a digital imager. The method includes generating a blended image by combining the multiple images, and executing an object detection algorithm on the blended image to locate and identify objects. The method includes determining a region of the identified object that contains a light source, and generating bounding box data around the light source region. The method includes communicating the bounding box data to the digital imager and updating the exposure time of the sensors in the bounding box region.
Abstract:
Systems and methods are disclosed for detecting light sources and selectively adjusting exposure times of individual sensors in image sensors. In one aspect, a method includes capturing multiple images of a scene using a digital imager. The method includes generating a blended image by combining the multiple images, and executing an object detection algorithm on the blended image to locate and identify objects. The method includes determining a region of the identified object that contains a light source, and generating bounding box data around the light source region. The method includes communicating the bounding box data to the digital imager and updating the exposure time of the sensors in the bounding box region.
Abstract:
A method for mapping an environment by an electronic device is described. The method includes obtaining a set of sensor measurements. The method also includes determining a set of voxel occupancy probability distributions respectively corresponding to a set of voxels based on the set of sensor measurements. Each of the voxel occupancy probability distributions represents a probability of occupancy of a voxel over a range of occupation densities. The range includes partial occupation densities.
Abstract:
Methods and apparatuses are described for wireless communications in which various association schemes may be performed for a machine type communication (MTC) device. In a long-term evolution (LTE) heterogeneous network, the MTC device may associate with a macro cell or a small cell using a narrowband MTC channel supported by the cells. Information about the MTC channel, including its frequency spectrum, may be transmitted to the MTC device using reserved bits in a physical broadcast channel (PBCH). Once the MTC device identifies the MTC channel, it may communicate with one or more cells during a frame or during a sub-frame. The MTC device may determine channel metrics of the cells from the MTC communication and may identify a cell with which to associate from the channel metrics. The association may be to a best downlink cell or a best uplink cell based on the operating profile of the MTC device.
Abstract:
A method performed by an apparatus is described. The method includes receiving map data that is based on first image data, second image data, and a similarity metric. The first image data can be received from a first vehicle and represent an object. The second image data can be received from a second vehicle and represent the object. The similarity metric can be associated with the object represented in the first image data and the object represented in the second image data. The method can also include storing, by a vehicle, the received map data and localizing the vehicle based on the stored map data.
Abstract:
A method performed by an apparatus is described. The method includes receiving a first set of object data corresponding to a first journey. The method also includes receiving a second set of object data corresponding to a second journey. The method further includes determining a similarity metric between the first set of object data and the second set of object data. The similarity metric indicates a distance between the first set of object data and the second set of object data for at least one object. The method additionally includes clustering the first set of object data and the second set of object data for the at least one object based on the similarity metric to produce at least one object cluster. The method also includes producing map data based on the at least one object cluster.
Abstract:
A method performed by an apparatus is described. The method includes receiving a first set of object data corresponding to a first journey. The method also includes receiving a second set of object data corresponding to a second journey. The method further includes determining a similarity metric between the first set of object data and the second set of object data. The similarity metric indicates a distance between the first set of object data and the second set of object data for at least one object. The method additionally includes clustering the first set of object data and the second set of object data for the at least one object based on the similarity metric to produce at least one object cluster. The method also includes producing map data based on the at least one object cluster.
Abstract:
A method for mapping an environment by an electronic device is described. The method includes obtaining a set of sensor measurements. The method also includes determining a set of voxel occupancy probability distributions respectively corresponding to a set of voxels based on the set of sensor measurements. Each of the voxel occupancy probability distributions represents a probability of occupancy of a voxel over a range of occupation densities. The range includes partial occupation densities.
Abstract:
Certain aspects provide a method for wireless communications by a first access point, comprising determining a first schedule of intervals for the first access point to communicate with a first group of one or more wireless devices, wherein intervals of the first schedule are synchronized with wake up or transmission cycles of the first group of one or more wireless devices and communicating with the first group of one or more wireless devices according to the first schedule.
Abstract:
A method performed by an apparatus is described. The method includes receiving a first set of object data corresponding to a first journey. The method also includes receiving a second set of object data corresponding to a second journey. The method further includes determining a similarity metric between the first set of object data and the second set of object data. The similarity metric indicates a distance between the first set of object data and the second set of object data for at least one object. The method additionally includes clustering the first set of object data and the second set of object data for the at least one object based on the similarity metric to produce at least one object cluster. The method also includes producing map data based on the at least one object cluster.