Abstract: The exemplary embodiment of the present disclosure relates to a camera module including a bobbin, a housing positioned at an outside of the bobbin, an elastic member coupled to the bobbin and the housing, a foreign object exhaust passage concavely formed at an upper surface of the housing, and an opening formed at the housing to open at least a part of the foreign object exhaust passage to an inside of the housing, wherein the foreign object exhaust passage is overlapped on at least a part of the housing-coupled elastic member to a vertical direction, whereby it is easy to wash foreign objects positioned between an elastic member and a housing to reduce an auto focus tilt defects generated after assembly.

Abstract: An image capture apparatus that detects, from an image, a subject area and a characteristic area within the subject area is disclosed. The image capture apparatus sets an AF area to the characteristic area and detects a defocus amount for the AF area and defocus amounts for peripheral areas of the AF area. The image capture apparatus corrects the defocus amount detected for the AF area based on the defocus amounts detected for the peripheral areas and adjusts focus of an imaging optical system based on the corrected defocus amount.

Abstract: Calibration devices for calibrating a camera, systems for computer-aided determination of hair colour information, and methods for calibrating a camera are provided herein. In an embodiment, a method for calibrating a camera includes recording a digital image of a piece of calibration information on a fibre from a plurality of fibres from natural hair or fibres that resemble natural hair by employing a camera. The fibre is identified in the digital image by employing a marker. A plurality of colour values are determined for a plurality of reference colours as the calibration information on the fibre in the digital image, wherein a reference colour value is assigned to each reference colour. The respective determined colour value for the plurality of the determined colour values is assigned to the respectively assigned reference colour value for the plurality of reference colour values.

Abstract: In one embodiment, an apparatus comprises processing circuitry to: receive, via a network interface, a video stream comprising a plurality of video frames; identify a plurality of dependencies among the plurality of video frames; identify, based on the plurality of dependencies, a first subset of video frames to be transmitted using a first transmission method and a second subset of video frames to be transmitted using a second transmission method, wherein the first subset of video frames and the second subset of video frames are identified from the plurality of video frames, and wherein the first transmission method provides a higher quality of service than the second transmission method; transmit, via the network interface, the first subset of video frames to a corresponding destination using the first transmission method; and transmit, via the network interface, the second subset of video frames to the corresponding destination using the second transmission method.

Abstract: An image capturing apparatus capable of focus detection includes a sensor including a plurality of pixels, the sensor being capable of changing an accumulation time of the pixels for each of a plurality of regions including the plurality of pixels, an accumulation control unit that, in accordance with a state or a setting of the image capturing apparatus, changes accumulation control of the pixels for each of the plurality of regions, and a defocus computation unit that calculates a defocus amount using signals from the pixels for which accumulation has been controlled by the accumulation control unit.

Abstract: Systems, methods and apparatuses for tracking at least a portion of a body by fitting data points received from a depth sensor and/or other sensors and/or “markers” as described herein to a body model. For example, in some embodiments, certain of such data points are identified as “super points,” and apportioned greater weight as compared to other points. Such super points can be obtained from objects attached to the body, including, but not limited to, active markers that provide a detectable signal, or a passive object, including, without limitation, headgear or a mask (for example for VR (virtual reality)), or a smart watch. Such super points may also be obtained from specific data points that are matched to the model, such as data points that are matched to vertices that correspond to joints in the model.

Abstract: There is described a method of labeling wood products moved across a handling area of a production line. The method generally has, using a camera, generating an image representing a wood product moving across the handling area at a first moment in time; using a controller, determining coordinates of the wood product at the first moment in time based on the image; and anticipating coordinates of the wood product at a second moment in time assuming an incremental movement of the wood product at a given speed from the determined coordinates of the wood product at the first moment in time; and using a light projector, projecting, at the second moment in time, a wood product label at the anticipated coordinates of the wood product at the second moment in time.

Abstract: In capturing images, a method applied in a camera device taking images of a dynamic scenes which provides compensation for blurring and lack of clarity caused by movement of objects within the scene. From images captured in preview mode, determining whether a target object is a dynamic object. A preset number of the preview images are stored as first images of a target object determined as being dynamic, and a second image is also taken, the second image being analyzed for an area of fuzziness. The camera device takes feature information from each first image and the feature information corresponding to the area of fuzziness of the second image and combines feature information having a highest similarity with the fuzzy area to generate a final target image with sharpness and full clarity, and outputting the target image.

Abstract: Examples are described of digital zoom retaining image characteristics such as sharpness, clarity, and/or contrast. In some aspects, a device can receive an image and can determine various image characteristic scores corresponding to digitally zoomed variants of the image having different zoom strengths. For instance, the device can determine a first image characteristic score for a first zoom strength and a second image characteristic score for a second zoom strength. The device can compare the image characteristic scores to an image characteristic threshold, and can select the highest zoom strength for which the corresponding image characteristic score is not below the image characteristic threshold. For example, the device can select the first zoom strength if the first image characteristic score meets or exceeds the image characteristic threshold while the second image characteristic score does not. The device can output image data corresponding to the image at the selected zoom strength.

Abstract: An object detection system may include an imager configured to generate image data indicative of an environment in which a machine is present, and a sensor configured to generate sensor data indicative of the environment in which the machine is present. The object detection system may further include an object detection controller including one or more object detection processors configured to receive an image signal indicative of the image data, identify an object associated with the image data, and determine a first location of the object relative to the position of the imager. The one or more object detection processors may also be configured to receive a sensor signal indicative of the sensor data, and determine, based at least in part on the sensor signal, the presence or absence of the object at the first location.

Abstract: The present disclosure provides an electronic device. The electronic device includes at least two camera modules, a motion sensor, and a control circuit configured to determine whether a first camera module of the at least two camera modules is activated, and when it is determined that the first camera module of the at least two camera modules is activated, control optical image stabilization of the first camera module using a signal received from the motion sensor.

Abstract: A visual search method, a computer device, and a non-transitory computer readable storage medium are provided. An ith image frame is received. The location and the classification of the subject in the ith image frame are extracted. A detection block corresponding to the subject is generated. In subsequent image frames of the ith image frame, the subject is tracked on the basis of the location of the subject in the ith image frame. The detection block is adjusted on the basis of the tracking result.

Abstract: Medical image data is identified, and a lung field region and an emphysema region in each of a plurality of tomographic images are extracted. A mechanism is provided, which is capable of calculating the ratio of the emphysema region to the lung field region, and displaying an image of the medical image data and a value representing the calculated ratio in association with each other.

Abstract: The object detection system includes a TOF sensor which outputs an image of a target space on the basis of a phase difference between reference light emitted toward the target space and reflected light from the target space, an object detection section which detects a position of an object present in the target space on the basis of the output image, an imaging conditions calculation section which calculates imaging conditions including at least one of an integration time and a light emission period of the TOF sensor on the basis of an image of the detected object, and an imaging conditions changing section which changes a configuration of the TOF sensor to the calculated imaging conditions, and the object detection section detects a position of the object on the basis of the image output under the changed imaging conditions.

Abstract: A real time assay monitoring system and method can be used to monitor reagent volume in assays for fluid replenishment control, monitor assays in real-time to obtain quality control information, monitor assays in real-time during development to detect saturation levels that can be used to shorten assay time, and provide assay results before the assay is complete, enabling reflex testing to begin automatically. The monitoring system can include a real time imaging system with a camera and lights to capture images of the assay. The captured images can then be used to monitor and control the quality of the staining process in an assay, provide early assay results, and/or to measure the on-site reagent volume within the assay.

Abstract: An information processing apparatus (2000) detects leaving of an object to be determined from an object queue (20) included in video data (12) generated by a camera (10). The information processing apparatus (2000) infers a global behavior of the object to be determined on the basis of a relationship between the object to be determined and another object (22) included in the object queue (20). The information processing apparatus (2000) determines whether or not the object to be determined has left the object queue (20) on the basis of the global behavior of the object to be determined.

Abstract: An object detection apparatus includes a first camera unit, a second camera unit, and a control unit. The first camera unit includes one or more cameras, and is configured to capture an image around a vehicle. The second camera unit includes one or more cameras, and is configured to capture an image of an area ahead of the vehicle. The control unit is configured to: determine a displacement of a feature point positioned in a common area from the image acquired via the first camera unit; determine a pixel displacement of the feature point in the image acquired via the second camera unit; and determine distance information to an object recognized in the image captured via the second camera unit based on the displacement of the feature point and the pixel displacement of the feature point.

Abstract: A method is disclosed to ensure that components in a complex system are correctly connected together. In one embodiment, such a method captures a visual image of a system made up of multiple components connected together with cables. The method analyzes the visual image to determine connections between the components. The method further builds a current model that represents the connections between the components. This current model is then compared to a previous model to find differences between the current model and the previous model. If differences exist, the method notifies a user of the differences. This may assist the user in identifying any incorrect connections between the components. A corresponding apparatus and computer program product are also disclosed.

Abstract: A system of this invention is directed to a bone cutting support system that properly indicates a bone cutting plane determined in advance to a doctor during surgery. The bone cutting support system includes a storage that stores 3D shape data of a surgery target bone in association with position data of a marker fixed to the surgery target bone, a bone cutting plane determiner that determines, based on the 3D shape data of the surgery target bone, a position and direction of a bone cutting plane or a bone cutting guide plane representing a plane to guide for cutting the surgery target bone, and a bone cutting plane display that displays the determined bone cutting plane based on an image obtained by capturing the marker fixed to the surgery target bone.

Abstract: An improved technique for determining height difference in patterns provided on semiconductor wafers uses real measurements (e.g., measurements from SEM images) and a height difference determination model. In one version of the model, a measurable variable of the model is expressed in terms of a function of a change in depth of shadow (i.e. relative brightness), wherein the depth of shadow depends on the height difference as well as width difference between two features on a semiconductor wafer. In another version of the model, the measurable variable is expressed in terms of a function of a change of a measured distance between two characteristic points on the real image of a periodic structure with respect to a change in a tilt angle of a scanning electron beam.