An image processing device includes a first image acquisition unit (10) that acquires first image data including one distance image among a plurality of distance images generated temporally continuously, a second image acquisition unit (20) that acquires second image data including one camera image among a plurality of camera images temporally continuously generated at a frame rate different from a frame rate of the first image data, and a processing unit (60) that performs processing of associating information of a distance image included in the first image data with the second image data on the basis of a time at which the first image data is generated and a time at which the second image data is generated.

A sensor device measuring a distance to an object includes: a light projection unit repeatedly emitting detection light toward the object; a light reception unit receiving reflected light of the detection light and outputting a binarized light reception signal (RT); a light projection oscillation unit controlling the emission of the detection light and outputting a start signal synchronized with the emission of the detection light; a counter measurement unit starting counting of the RT when receiving the RT and the start signal, and outputting a stop signal corresponding to a feature point of the RT; a delay line measurement unit outputting a delay line output signal corresponding to the delay time of the RT near the feature point of the RT when receiving the RT and the stop signal; and a distance calculation unit calculating the distance to the object based on the delay line output signal.

A sensor device measuring a distance to an object includes: a light projection unit repeatedly emitting detection light toward the object; a light reception unit receiving reflected light of the detection light and outputting a binarized light reception signal (RT); a light projection oscillation unit controlling the emission of the detection light and outputting a start signal synchronized with the emission of the detection light; a counter measurement unit starting counting of the RT when receiving the RT and the start signal, and outputting a stop signal corresponding to a feature point of the RT; a delay line measurement unit outputting a delay line output signal corresponding to the delay time of the RT near the feature point of the RT when receiving the RT and the stop signal; and a distance calculation unit calculating the distance to the object based on the delay line output signal.

An object detection system includes a light emitter, an optical sensor, a controller, and a signal processor. The controller controls the light emitter and the optical sensor to cause range segment signals to be outputted from the optical sensor for corresponding range segments. The signal processor includes: a target object information generator that includes a plurality of generators (a first generator through a fifth generator) capable of operating in parallel and generates items of target object information indicating features of target objects for the range segments; and storage that stores the items of target object information. The target object information generator compares a past one of the items of target object information stored in the storage with a feature of a current one of the target objects detected by the optical sensor to generate a corresponding one of the items of target object information.

Techniques of deriving audio signals using frequency modulated continuous-wave (FMCW) LIDAR use an acceleration-based algorithm in which an audio signal is based on a difference in velocity between two up-chirps or two-down-chirps. Such an acceleration-based algorithm takes less computation, results in fast processing, boosts the high frequency component of the audio signals which the velocity-based algorithm lacks, and improves the subjective intelligibility. For example, in the acceleration-based algorithm, the DC components may be safely ignored in many cases. In such cases, the system does not require a band-pass filter as in the conventional systems, thus reducing computational burden. Moreover, the acceleration-based algorithm emphasizes high frequencies that form a more realistic depiction of human speech.

Techniques of deriving audio signals using frequency modulated continuous-wave (FMCW) LIDAR use an acceleration-based algorithm in which an audio signal is based on a difference in velocity between two up-chirps or two-down-chirps. Such an acceleration-based algorithm takes less computation, results in fast processing, boosts the high frequency component of the audio signals which the velocity-based algorithm lacks, and improves the subjective intelligibility. For example, in the acceleration-based algorithm, the DC components may be safely ignored in many cases. In such cases, the system does not require a band-pass filter as in the conventional systems, thus reducing computational burden. Moreover, the acceleration-based algorithm emphasizes high frequencies that form a more realistic depiction of human speech.

A drive control system (S) includes a measurement portion (1) configured to detect an obstacle (R) in a transportation vehicle (T), and a load collapse determination portion (4) configured to acquire an arrangement of a transportation target (C) loaded on the transportation vehicle (T) based on measurement data of the measurement portion (1) to determine a load collapse of the transportation target (C) based on a change in the arrangement over time.

A localization method includes scanning a surrounding space by using laser outputted from a reference region; processing spatial information about the surrounding space based on a reflection signal of the laser; extracting feature vectors to which the spatial information has been reflected by using a deep learning network which uses space vectors including the spatial information as input data; and comparing the feature vectors with preset reference map data, and thus estimating location information about the reference region.

A transmission line monitoring system and central processing facility are used to determine the geometry, such as a height, of one or more conductors of a power transmission line and real-time monitoring of other properties of the conductors.

A transmission line monitoring system and central processing facility are used to determine the geometry, such as a height, of one or more conductors of a power transmission line and real-time monitoring of other properties of the conductors.