Abstract: An electro-optical module (EOM) included within an enclosure is provided. The EOM comprises at least two camera modules, and configured to determine depth of a target by using a block matching algorithm operative to match pixels derived from an image captured by one of the camera modules with pixels derived from an image captured by another of the two camera modules. The EOM is characterized in that it comprises: a first isolating material located between the EOM and its enclosure, and configured to prevent structural forces from being developed due to deformation of the EOM enclosure; a main processor baseboard PCB to which each of the camera modules is connected; and one or more flat cables connecting the EOM enclosure with the main processor baseboard PCB, wherein the one or more flat cables are placed in an “s” shape within the EOM enclosure.

Abstract: A computational platform and a method for use in a process of matching pairs of pixels, wherein each of the members of a pixel's pair belong to another image captured by a different image capturing sensor, and wherein the computational platform comprises at least one processor configured to carry out a process of matching pairs of pixels based on selecting a pixel mask to be used by selecting neighboring pixels of a given pixel from among all of its neighboring pixels, will be used for the matching process of said given pixel with the other member of its pixel's pair.

Abstract: A method for use in a stereoscopic image generating system, wherein the image generating system comprises a hardware module associated with at least one pair of image capturing devices, at least one memory means and at least one processor, wherein information retrieved from the capturing devices is processed by the at least one processor, which is configured to implement a hardware module stereo algorithm for identifying objects included in the captured scene at a distance that is equal to or greater than a minimal distance defined by the geometry and disparity range of said hardware module, and wherein the at least one processor is further configured to implement a software stereo algorithm adapted to identify objects included in the captured scene at a distance that is less than the minimal distance required for detecting objects by the hardware module stereo algorithm.

Abstract: A pattern projector is disclosed. The pattern projector comprises a light source, a projection lens, a mask and configured to enable the at least one projection lens to illuminate a target while projecting the pre-defined pattern thereat, and at least one holder, and wherein the pattern projector is characterized in that the at least one light source is a wide area light source, and wherein the area of the at least one mask or the at least one mask active area, is smaller than the area of the at least one light source, enabling to refrain from applying condenser optics or focusing optics between the at least one light source and the at least one mask.

Abstract: A method is described for processing data retrieved from two image capturing sensors, by filling missing disparity values of pixels included in holes comprised in the retrieved data.

Abstract: A system configured to operate in an unknown, possibly texture-less environment, with possibly self-similar surfaces, and comprising a plurality of platforms configured to operate as mobile platforms, where each of these platforms comprises an optical depth sensor, and one platform operates as a static platform and comprising at least one optical projector. Upon operating the system, the static platform projects a pattern onto the environment, wherein each of the mobile platforms detects the pattern or a part thereof by its respective optical depth sensor while moving, and wherein information obtained by the optical depth sensors, is used to determine moving instructions for mobile platforms within that environment. Optionally, the system operates so that every time period another mobile platform from among the plurality of platforms, takes the role of operating as the static platform, while the preceding platform returns to operate as a mobile platform.

Abstract: A method and a computational module are provided for carrying out a quantization process of a plurality of channels carrying data received from an image capturing sensor. The computational module comprises: at least one array of processors, configured to a) retrieve data from: a1) a neural network graph, a2) a dataset associated with a data and a3) parameters' values of a neural network model; b) carry out a dynamic range calibration process for the channels received and using the neural network graph for deriving grouping constrains associated with respective channels; c) carry out a grouping optimization based on results obtained for each channel from its respective dynamic range calibration and its grouping constrains; d) arrange the channels so that channels having similar grouping constrains are grouped together into one output channel; and e) calculate required quantization parameters for carrying out a quantization process of the output channels.

Abstract: A method is provided for calibrating a structured light system. The structured light system comprises, a camera, a processor and a projector that emits light at an unknown pattern. According to this method, the projector emits an unknown pattern at two different distances relative to the camera's location, and the camera captures the pattern that was projected at the different distances The processor then determines the vertical disparity between the two captured images and estimates a relative orientation between the camera and the projector. This estimation in turn is applied in the calibration of the structured light system.

Abstract: An autonomous mobile platform is described. The autonomous mobile platform is configured for use in road monitoring, and comprising: a scanning module configured to be used for road scanning in order to enable identifying hazards associated with the road being scanned; a location finder, configured to determine locations of hazards identified at the road being scanned; and at least one transmitter comprised in a respective autonomous mobile platform, and configured to transmit data derived by the scanning module from the road scanning.

Abstract: A method and apparatus for generating a three-dimensional depth map, are provided. The method comprising the steps of: (i) illuminating a target by a pattern projector having background intensity or by a combination of a pattern projector which does not have a background intensity operative together with a flood projector; (ii) capturing at least one image that comprises one or more objects present at the illuminated target; (iii) converting the at least one captured image into data; (iv) processing the data received from the conversion of the at least one captured image while filtering out the projected pattern from the processed data; (v) detecting edges of at least one of the one or more objects present at the illuminated target; and (vi) generating a three-dimensional depth map that comprises the at least one of the one or more objects whose edges have been determined.

Abstract: A central unit is provided which is operative in a system that comprises a plurality of moveable devices, each comprising an optical depth sensor. The central unit comprises a processor adapted to: divide the moveable devices into a plurality of groups, wherein each of the groups is characterized by a specific wavelength range at which all projecting modules associated with the optical depth sensors of the moveable devices belonging to that group, are operative; establish a time frame within which each of the optical depth sensors of the moveable devices will operate, wherein the time frame comprises a plurality of time slots; and associate at least two of the moveable devices with a single time slot, wherein each of the at least two moveable devices belongs to a different group than the other.

Abstract: An optical passive stereo assembly for generating a three-dimensional image, the optical assembly comprising: two image capturing devices each mounted within the optical passive stereo assembly in a skewed position to the other with respect to the horizontal plane; a processor configured to: process data retrieved from a plurality of pixels comprised within images captured by the two image capturing devices, and generate a point cloud, being a set of data points in a 3D space retrieved from the tilted coordinate system (X?, Y?, Z?); apply a 2D rotation in the X-Y plane to the point cloud, thereby converting the coordinate system of the resulting point cloud to a conventional cartesian coordinate system (X, Y, Z), to enable generating the three-dimensional image.

Abstract: A method and a stereoscopic apparatus configured to determine an exposure time period for capturing images. The apparatus comprises at least one image capturing device for capturing pairs of images; a processor configured to: calculate a texture-signal-to-noise ratio (TSNR) metric based on information derived from a pair of captured images; calculate an image saturation metric based on that pair of captured images; calculate a value for an exposure duration that will be implemented by the at least one image capturing device when another pair of images are captured; provide the value of the calculated exposure time period to each at least one image capturing device; and wherein the at least one image capturing device is configured to capture at least one image of the target while implementing each the respective calculated value of the exposure time period provided to the corresponding one of the at least one image capturing device.

Abstract: An optical collimating unit is provided that comprises a laser unit, and a lens having three optical surfaces, being a first refractive surface, a second reflective surface and a third refractive surface. Also provided is a light projection device comprising an optical collimating unit that comprises a laser unit, a lens and an optical component configured to shape laser beams being emitted into respective desired light patterns.

Abstract: A method is provided for assembling a 3D sensing apparatus that comprises at least two projectors, wherein the assembling of the apparatus is carried out by ensuring that a pattern formed from a combination of images projected by each of the at least two projectors, is not formed along an epi-polar line or part thereof more than once. The method comprises the steps of: placing the at least two projectors at initial approximate physical positions within the 3D sensing apparatus; and, placing one or more projectors' protectors on top of the at least two projectors, thereby changing the projectors initial positions and automatically positioning them accurately in their pre-defined position and orientation by using the one or more projectors' protectors.

Abstract: A system and a method on an integrated circuit are provided herein. The system may include: a plurality of defined data processing dedicated areas to perform computational functions relating to a corresponding plurality of natural user interface features, to obtain the plurality of user interface features based on scene features detected by a plurality of sensors within a defined period of time; a central processing unit configured to carry out software instructions to support the computational functions of the dedicated areas; and at least one defined area for synchronized data management, to receive signals corresponding to detected scene features from the plurality of sensors and to route the signals to suitable dedicated areas of the plurality of dedicated areas to provide real-time acquiring of user interface features.

Abstract: An optical module and a method for its used are provided. The optical module comprises: an image capturing device; an illuminating device; a position measurement unit and a processor configured to: a) identify objects included in at least one frame that has been captured by the image capturing device; b) determine expected position of the one or more identified objects based on data received from the position measurement unit; and c) control operation of the at least one illuminating device while capturing a new image, to illuminate only part of the field of view of the target being acquired by the at least one image capturing device, wherein the one or more identified objects are included.

Abstract: A method and apparatus are provided for generating a three dimensional image, wherein the method includes: illuminating a target; capturing an image that comprises an object present at the illuminated target; converting the captured image into data and processing it to determine depth of the object; and generating a three dimensional image of the object whose depth has been determined. Preferably, the illumination intensity applied while illuminating the target, is determined based on the current intensity of ambient light at the target.

Abstract: A method is provided for use in a stereoscopic image generating system, the system including at least two image capturing sensors and at least one aggregation processor. The at least one aggregation processor is configured to: receive data associated with an image captured by the image capturing sensors; calculate aggregation results for a pre-defined number of disparity levels based on data received from one of the at least two image capturing sensors; estimate aggregation results for data received from another image capturing sensor; and combine the calculated results with the estimated results.

Abstract: A method is provided for reconstructing a three dimensional image, comprising: providing a pair of stereoscopic images captured by two image capturing devices; retrieving disparity data from the pair of stereoscopic images; using retrieved disparity data to determine contours of an object present in the pair of the stereoscopic images captured; selecting a pixel belonging to that object; establishing a search area at the vicinity of the selected pixel; determining values for various disparity candidates, wherein the determined values correspond to one or more chosen hypothesis associated with the search area; testing the one or more chosen hypothesis and selecting an hypothesis which best fits the selected pixel and its neighboring pixels; executing a stereo matching algorithm using data retrieved from the captured images while using the values of disparity candidates that correspond to the chosen hypothesis; and reconstructing the three dimensional image based on the results obtained.