Abstract:
A method of analyzing images over time is provided herein. The method includes: capturing a plurality of images each associated with specified objects in specified locations such that a specified area is covered; specifying regions of interest (ROI) in each of the captured images; repeating the capturing with at least one of: a different location, a different orientation, and a different timing such that the captured images are associated with the specified covered area; and comparing the captured imaged produced in the capturing with the captured imaged produced in the repeating of the capturing to yield comparison between the captured objects by comparing specified ROI.

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     This application is the U.S. national phase of PCT application PCT/IB2010/054538, filed 7 Oct. 2010, published 14 Apr. 2011 as WO 2011/042876, and claiming priority to U.S. Provisional Patent Applications No. 61/249,263 filed Oct. 7, 2009; 61/286,403 filed Dec. 15, 2009; 61/329,109 filed Apr. 29, 2010; 61/330,997 filed May 4, 2010; 61/333,809 filed May 12, 2010; and 61/347,468 filed May 24, 2010. 
    
    
     BACKGROUND 
     1. Technical Field 
     The present invention relates to image and video processing and more particularly, to such processing based on time-based changes. 
     2. Discussion of the Related Art 
     Using images of scenes taken on different time slots is a well-known method to detect, classify, and analyze changes to the scene or specific objects contained therein. Changes analysis may have further applications that may vary, according to the scope of the time-space that is being monitored. 
     The introduction of ubiquitous cellular communication devices equipped with imaging capabilities, some with positioning means, poses a challenge for a system and method for controlling these devices in an efficient manner for configuring them for object analysis that is changes based on one hand and has a wide span of applications, on the other hand. 
     BRIEF SUMMARY 
     One aspect of the invention provides a method of analyzing images over time. The method includes: capturing a plurality of images each associated with specified objects in specified locations such that a specified area is covered; specifying regions of interest (ROI) in each of the captured images; repeating the capturing with at least one of: a different location, a different orientation, and a different timing such that the captured images are associated with the specified covered area; and comparing the captured imaged produced in the capturing with the captured imaged produced in the repeating of the capturing to yield comparison between the captured objects by comparing specified ROI. 
     Other aspects of the invention may include a system arranged to execute the aforementioned methods and a computer readable program configured to execute the aforementioned methods. These, additional, and/or other aspects and/or advantages of the embodiments of the present invention are set forth in the detailed description which follows; possibly inferable from the detailed description; and/or learnable by practice of the embodiments of the present invention. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       For a better understanding of embodiments of the invention and to show how the same may be carried into effect, reference will now be made, purely by way of example, to the accompanying drawings in which like numerals designate corresponding elements or sections throughout. 
       In the accompanying drawings: 
         FIG. 1  is a flowchart of acts performed in accordance with an exemplary embodiment of the invention; 
         FIG. 2  is a scheme describing the system and process in accordance with an exemplary embodiment of the invention; 
         FIG. 3  is a high level block diagram illustrating a data processing and presenting according to some embodiments of the invention; 
         FIG. 4A  is a scheme describing a system and process in accordance with an exemplary embodiment of the invention; 
         FIG. 4B  is a side view of a system and process in accordance with an exemplary embodiment of the invention described in  4 A; 
         FIG. 5  is a flowchart of acts performed in accordance with an exemplary embodiment of the invention; 
         FIG. 6  is a scheme describing a system and process in accordance with an exemplary embodiment of the invention; 
         FIG. 7  is a scheme describing a system and process in accordance with an exemplary embodiment of the invention; 
         FIG. 8  is a scheme describing a system and process in accordance with an exemplary embodiment of the invention; 
         FIG. 9  is a scheme describing a system and process m accordance with an exemplary embodiment of the invention; 
         FIG. 10  is a scheme describing a system and process in accordance with an exemplary embodiment of the invention; 
         FIG. 11  is a scheme describing a system and process in accordance with an exemplary embodiment of the invention; 
         FIG. 12  is a scheme describing a system and process in accordance with an exemplary embodiment of the invention; 
         FIG. 13  is a scheme describing a system and process in accordance with an exemplary embodiment of the invention; and 
         FIGS. 14A and 14B  are a scheme describing a system and process in accordance with an exemplary embodiment of the invention. 
         FIG. 15  is a schematic illustration of an information display system 
     
    
    
     The drawings together with the following detailed description make apparent to those skilled in the art how the invention may be embodied in practice. 
     DETAILED DESCRIPTION 
     With specific reference now to the drawings in detail, it is stressed that the particulars shown are by way of example and for purposes of illustrative discussion of the preferred embodiments of the present invention only, and are presented in the cause of providing what is believed to be the most useful and readily understood description of the principles and conceptual aspects of the invention. In this regard, no attempt is made to show structural details of the invention in more detail than is necessary for a fundamental understanding of the invention, the description taken with the drawings making apparent to those skilled in the art how the several forms of the invention may be embodied in practice. 
     Before explaining at least one embodiment of the invention in detail, it is to be understood that the invention is not limited in its application to the details of construction and the arrangement of the components set forth in the following description or illustrated in the drawings. The invention is applicable to other embodiments or of being practiced or carried out in various ways. Also, it is to be understood that the phraseology and terminology employed herein is for the purpose of description and should not be regarded as limiting. 
     To facilitate understanding the present invention, the following glossary of terms is provided. It is to be noted that terms used in the specification but not included in this glossary are considered as defined according the normal usage of the computer science art, or alternatively according to normal dictionary usage. 
     The term “DB” as used herein in this application, is defined as database 
     The term “GIS” as used herein in this application, is defined as a computer system designed to allow users to collect and/or manage and/or analyze spatially referenced information. 
     The term “surface objects” as used herein in this application, is defined as objects that are on the surface of a planet such as buildings, roads, canals, fields. 
     The term “surface data” as used herein in this application is defined as information gathered on surface objects such as aerial images, satellite images, ground images, and images taken with a handheld camera or camera-phone, GIS information, LIDAR data, Radar scans. 
     The term “image” as used herein in this application is defined as visual representation that can be presented on two dimensional or three dimensional surfaces. Images can be taken in any part of the electromagnetic spectrum such as visible light, infrared, ultraviolet, X-rays, Terahertz, Microwaves, and Radio frequency waves. An Image could be taken from one or more sensors or with one sensors with multiple lenses in order to create a 3 dimensional image. 
     The term “photo” as used herein in this application is defined as image in the visible light. 
     The term “DSM” as used herein in this application, is defined as a topographic elevation model of the Earth surface that provides a geometrically representation for the purpose of overlaying the model with a wide range of GIS data. DSM provides a surface elevation of every natural and artificial feature visible within the image area. 
     The term “DEM” as used herein in this application, is defined as a digital representation of a continuous variable over a two-dimensional surface by a regular array of z values referenced to a common datum. 
     The term “DTM” as used herein in this application, is defined as Digital Terrain Model is a 3D representation of the Earth&#39;s surface. Its construction includes a height model (DEM) and overlaid with map data relating to features on the surface (Map Data or Aerial Photograph). 
     The term “INS” as used herein in this application, is defined as a navigation aid that uses a computer, motion sensors (accelerometers) and rotation sensors (gyroscopes) to continuously calculate via dead reckoning the position, orientation, and velocity (direction and speed of movement) of a moving object without the need for external references. 
     The term “GPS” as used herein in this application, is defined as A system based on satellites that allows a user with a receiver to determine precise coordinates for their location on the earth&#39;s surface. 
     The term “Micronavigation” as used herein in this application, is defined as a method based on visual objects that allows a user to determine precise coordinates for their location on the earth&#39;s surface in a precision that is higher than of a GPS system. 
     The term “Real Time Map” as used herein in this application, is defined Map having layer that are updated in a latency that is lower than the latency needed to benefit from the map considering the changes in the layer. For example a real time traffic jam map is a map that is updated for at least the last hour as that jams might be gone in an hour 
     The term “GPU” as used herein in this application, is defined as an apparatus adapted to reduce the time it takes to produce images on the computer screen by incorporating its own processor and memory, having more than 16 CPU cores, such as GeForce 8800. 
     The term “Keypoint” as used herein in this application, is defined as interest points in an object. For example, in the SIFT framework, the image is convolved with Gaussian filters at different scales, and then the difference of successive Gaussian-blurred images are taken. Keypoints are then taken as maxima/minima of the Difference of Gaussians. Such keypoint can be calculated for the original image or for a transformation of the original image such as an affine transform of the original images. 
     The term “Keypoint descriptor” as used herein in this application, is defined as a descriptor of a key point. For example, in the SIFT framework the feature descriptor is computed as a set of orientation histograms on neighborhoods. The orientation histograms are relative to the keypoint orientation and the orientation data comes from the Gaussian image closest in scale to the keypoint&#39;s scale. Just like before, the contribution of each pixel is weighted by the gradient magnitude, and by a Gaussian with a 1.5 times the scale of the keypoint. Histograms contain 8 bins each, and each descriptor contains an array of 4 histograms around the keypoint. This leads to a SIFT feature vector with (4×4×8=128 elements). 
     The term “Visual content item” as used herein in this application, is defined as an object with visual characteristics such as An image file like BMP, JPG, JPEG, GIF, TIFF, PNG files; a screenshot; A video file like AVI, MPG, MPEG, MOV, WMV, FLV files or a one or more frame of a video. 
     The term LIDAR as used herein in this application is defined as is an optical remote sensing technology that measures properties of scattered light to find range and/or other information of a distant target. The prevalent method to determine distance to an object or surface is to use laser pulses 
     The term “Visual object” as used herein in this application, is defined as a content that includes visual information such as Visual content item, images, photos, videos, IR image, magnified image, an image sequence or TV broadcast. 
     The term “Camera” as used herein in this application is defined as means of capturing a visual object 
     The term Terminal as used herein in this application, is defined as an apparatus adapted to show visual content such as a computer, a laptop computer, Mobile phone or a TV. 
     The term Visual similarity as used herein in this application, is defined as the measure of resemblances between two visual objects that can be comprised of:
         The fit between their color distributions such as the correlation between their HSV color histograms;   The fit between their texture;   The fit between their shapes;   The correlation between their edge histograms;   Face similarity;   methods that include local descriptors and/or keypoints such as SIFT see (en.wikipedia.org/wiki/Scale-invariant feature transform), ASIFT, SURF and MSR.       

     The term “Visual analysis” as used herein in this application, is defined as the analysis of the characteristics of visual objects such, as visual similarity, coherence, hierarchical organization, concept load or density, feature extraction and noise removal 
     The term “Sound analysis” as used herein in this application, is defined as the analysis of audio waves such as speech recognition, song recognition, and sentiment recognition 
     The term “Text similarity” as used herein in this application, is defined as Measure the pair-wise similarity of strings. Text similarity can score the overlaps found between two strings based on text matching. Identical strings will have a score of 100% while “car” and “dogs” will have close to zero score. “Nike Air max blue” and Nike Air max red” will have a score which is between the two. Further string similarity metrics are described in http://en.wikipedia.org/wiki/String metric. 
     The term “Regular expression” as used herein in this application, is defined as a string that provides a concise and flexible means for identifying strings of text of interest, such as particular characters, words, or patterns of characters. See http://en.wikipedia.org/wiki!Regular_expression. 
     The term “Text analysis” as used herein in this application, is defined as the analysis of the structural characteristics of text, as text similarity, coherence, hierarchical organization, concept load or density. (See google.com/search?h1=en&amp;safe=off&amp;r1z=1CICHMG_eniL291L303&amp;q=define:text+analysis&amp;btnG=Search). Text analysis can use regular expressions. 
     The term “LPR” as used herein in this application, is defined as: license plate recognition as described in en.wikipedia.org/wiki/Automatic_number_plate_recognition. 
     The term “OCR” as used herein in this application, is defined as The electronic identification and digital encoding of printed or handwritten characters by means of an optical scanner and specialized software 
     The term “Symbol analysis” as used herein in this application, is defined as analysis of symbolic data such as: OCR, LPR, hand write recognition, bar-code recognition, and QR code recognition. 
     The term “Capturing data” as used herein in this application, is defined as data taken while capturing a visual object such as: X-Y-Z coordinates; 3 angles; Manufacturer; Model; Orientation (rotation) top-left; Software; Date and Time; YCbCr Positioning centered; Compression; x-Resolution; y-Resolution; Resolution Unit; Exposure Time; FNumber; Exposure Program; Exif Version; Date and Time (original); Date and Time (digitized); Components Configuration Y Cb Cr -; Compressed Bits per Pixel; Exposure Bias; Max Aperture Value; Metering Mode Pattern; Flash fired or not; Focal Length; Maker Note; Flash Pix Version; Color Space; Pixel X Dimension; Pixel Y Dimension; File Source; Interoperability Index; Interoperability Version; derivatives of the above such as acceleration in the X-axis; The term “Capturing data analysis” as used herein in this application, is defined as the analysis of Capturing data. 
     The term “Service location” as used herein in this application, is defined as a physical place where objects can be serviced and/or fixed such as a mobile carrier service center. 
     The term “Location based analysis” as used herein in this application, is defined as analysis of local data such as GPS location, triangulation data, RFID data, and street address. Location data can for example identify the service location or even the specific part of the service location in which the visual object was captured. 
     The term “Content analysis” as used herein in this application, is defined as the combination of text analysis, visual analysis, symbol analysis, location based analysis, Capturing data analysis, sound analysis and/or analysis of other data such as numerical fields (price range), date fields, logical fields (Female/male), arrays and structures, and analysis history. 
     The term “Content Match” as used herein in this application, is defined as a numerical value that describes the results of the content analysis that computes the similarity between one or more visual objects, or a logical value that is true in case said similarity is above a certain threshold. 
     The term “Data Clustering methods” as used herein in this application, is defined as the assignment of objects into groups (called clusters) so that objects from the same cluster are more similar to each other than objects from different clusters. Often similarity is assessed according to a distance measure. See en.wikipedia.org/wiki/Data_clustering 
     The term “Driver warning” as used herein in this application, is defined as a warning comprising: Audio alert such as a beep sound; A Visual alert such as a red light and/or a text such as: “stop”, “slow down”, “approaching destination”, “pedestrian are crossing”, “crossing border”; A Tactile feedback such as vibrations; 
     The term “Driving intervention” as used herein in this application, is defined as automatic driving operation such as: Braking; Slowing down; Complete stop; Taking a right turn; Taking a left turn; Turning lights on; Tightening the seat belt; 
     The term “Server reaction” as used herein in this application, is defined as an action performed on a remote server such as sending a message such as an SMS to a specific person or sending a team to a specific location. 
     The term “System reaction” as used herein in this application, is defined as a driver warning, a driving intervention or server reaction combination of them. 
       FIG. 1  is a flowchart of acts performed in accordance with an exemplary embodiment of the invention; and 
     System  100  performs the following steps: 
     Surface data is captured  200  in manner further described in  FIG. 2 . Optionally, the Surface data is compared  300  to surface data taken or created at an earlier time. And the difference results are presented  350  as further described in  FIG. 3 . 
     In case changes are detected further actions  400  can be taken such as Ordering system  222  such as plane to capture another image of the changed object such as: 
     1. Taking
         Enlarged image Closer   image Oblique(diagonal)   An image of different modality than the original one such as IR image in case a visible range image was originally taken   Same image to verify the change       

     2. Monitor system  200  by reporting an abnormal number of changes. 
     3. Performing an onsite manned or unmanned inspection of the object from the ground to further check/verify reported changes 
     This will be more beneficial in case comparison is taken in “real time” such as time short enough to perform action  400  in the same session such as the same flight session. 
       FIG. 2  is a scheme describing the system and process in accordance with an exemplary embodiment of the invention. System  200  performs the process of gathering surface data using: 
     1) A. devices such as: 
     a) A camera system  212  comprising a camera  216  and optionally a GPS 
       214  and/or INS units  215 . It is to be noted that preferably there are similar systems such as  213  capturing data at the same time. In a similar manner there could be further similar system such  218  and/or  219  gathering data at the same time and/or being at the same location and/or gathering data of the same surface object. 
     b) A LIDAR  218  or RADAR system using pulses of waves to capture data. 
     c) A mobile camera phone  219 , preferably one that resides in an ordinary mobile phone or a navigation system, and preferably one that is able to provide further geo-location data such as GPS or other triangulation data. 
     2) Airborne Platform to carry said devices such as:
         a) An airplane  222  b) An airship  226     c) A satellite  224         

     3) A surface level platform such as:
         a) A vehicle such as car  110  or a motorcycle in which case  219  can be a navigation system placed on the inner part of a car windows and having a camera and preferably captures visual object while moving. Optionally car  110  carries a camera such as  122  close to it front or back license plate. Alternatively, camera  122  is installed on the front and/or back license plate of the car.   b) A building  234  c) A person  236     d) A human body part such as ear  237  having an earpiece  238  equipped with camera  122         

       FIG. 3  is a high level block diagram illustrating a data processing and presenting according to some embodiments of the invention. 
     The inputs for system  250  are comprised of: 
       260 : DEM and/or DSM and/or DTM collected using systems such as  200   
       252 : Surface data 
       254 : images, and preferably models that include images and X-Y-Z/Polar coordinates for each pixel/object in said image 
       256 : LIDAR or Radar data 
       258 : GPS and/or INS data such as  6  dimensional data comprised of latitude, longitude, height, pitch, roll, and yaw. 
       264  Visual object 
       266  Capturing data 
       268  Location data 
       270  Symbolic data 
       272  Textual data 
       274  Historical data, such as the last object identified at the same coordinates. 
       276  sound waves 
     Said inputs and historical data of the same location and/or object are processed by subsystem  300 . Subsystem  300  is preferable using one or more GPU&#39;s  310  as processing of large data sets requires a significant amount of computation and the usage of parallel algorithms such as keypoint descriptors comparison. 
     System  300  is further comprised of two subsystems: 
     Subsystem  320  that does content analysis such change detection between two or more data sets such as: 
       322  keypoint based comparison methods such as SIFT Using methods such as Scale-invariant feature transform or similar methods such as GLOH (Gradient Location and Orientation Histogram), PCA-SIFT and MSR. Such method usually use keypoint localization step, an later on compare many keypoint descriptors in one object to a plurality of keypoint descriptors in another object and hence require quick computation in order to compare an object to a plurality of object within a response time an ordinary user would expect. The higher the number or the percentage of keypoint descriptors in a first object than match (exactly or approximately) keypoint descriptors in a second object the higher is the similarity between the two objects. Preferably the module uses Keypoints of transformed object based methods. Such transformation can even further use  250  data such as  258  and/or  260  to create estimated needed compensation transform such is there is a 5° deviation between two images of the same building it can correct the resulting keypoint accordingly. Using methods such as Haar wavelet transform. Comparing the color histograms of the object to other color histograms. The methods can be used separately, one after another or in parallel. In case a heavily computational method such as (a) is used it is advisable to use a GPU such as  310  to attain a reasonable response time and to run parallel algorithms. 
       324  correlation based methods such as  2 D correlation 
     Subsystem  340  used to filter in the more important changes comprising: 
       342  Object subtraction module, used to ignore object such as trees, and water and grass. 
       344  a module to ignore mobile object such as cars or people using (their calculated speed, size, or the fact they do not reappear in two consecutive images or two image modalities) 
       346  a module to focus on object of interest such as houses using their visual characteristics (such as shape, color, texture, known patterns, edges) 
     Subsystem  350  presents the data in a format useful for the intended applications such as: 
       352 : Photo with marked changes from previous photo and preferably digital signature in order to be legally accepted as evidence. 
       354 : GIS output. 
       356 : A report of unauthorized improvements done to objects such as adding a room to a house. 
       358 : agricultural data such growth rate of crops 
       360 : 3D views such as Urban maps 
     Reports as shown in  1240  and  1260   
       FIG. 4A  is a front view of a system and process in accordance with an exemplary embodiment of the invention. 
     System  490  is located on the inner part of a vehicle such as  110 . It can be mounted on the front window  442  or the back window  444  of the vehicle. The system is comprised of: 
     Car mount  450  further comprising of: 
     Suction cup  456 —a device, usually made of rubber or plastic, that sticks to smooth, nonporous surfaces such as  442 . This device can be replaced by an adhesive unit. 
     Arm  454  attached to both  456  and  452 . Sometimes arm  454  is flexible. 
     A cradle  452  that can grip a device such  120 . Cradle is adapted to enable repeated quick and repeatable mounting and un-mounting(for example in less than 5 seconds), for example by using side holders  453  that grab device  120  from its left and right side. In some cases one of the corners of cradle  452  is eliminated or cut to clear line of sight for camera  122  and/or  128 . 
     Device  120  is a device having a processing unit, such as a smart-phone such as an iPhone device. Sometimes device  120  is mobile and sometimes it is stationary. Sometimes device  120  has multiple cores (such as a graphic card) that enable executing parallel algorithms. Sometimes device  120  has an internal and/or external antenna such as  121 . Antenna  121  can wirelessly connect the device to a public network such the Internet and thus transmit the information gathered by device to a remote server and/or to other users such as other users of a device such as  120  and thereby share that information. 
     Device  120  can have one back side camera such as  122  or additional camera such as  128 . Sometimes device  120  runs a second application such as a Navigation application in parallel to performing the process of  FIG. 5 . Sometimes though, camera is actively capturing images, device  120  is adapted not to display the captured image. 
     Sometimes Device  120  uses means for receiving power such as cable  462  that connects to the a car lighter socket such as  464 . 
     Device  410  is a media player such as car radio. 
       FIG. 4B  is a side view of a system and process in accordance with an exemplary embodiment of the invention described in  4 A 
     The vehicle&#39;s driving direction is defined in  430 . 
     The vehicle has a front window  442 , a back window  444 , and a roof  446 . 
     The vehicle is driven by driver  140 , drivers eye is marked  142 . 
     Sometimes device  120  has additional sensors  124 , 126 , these sensors can be:
         Microphone   Accelerometer   Compass   GPS or AGPS receiver   Magnetic sensors   Proximity sensor   Capacitive sensors   Finger print sensor   Chemical sensor   Machine olfaction sensor   CO2 sensor   Bio-sensors   A sensor matrix of any of the above   Temperature sensor either one that requires contact with the measured medium or one capable of remote measurement of temperature       

     For example a microphone can be used to capture sound waves indicating a car problem. 
     In Another example motion sensor  124  and/or camera  128  can be used as a car theft alarm, hence in case the car is moved while its owners are out of the car, it will produce an alarm sound and/or call and/or SMS its owner and or the police. 
     A front camera such as  128  can capture a visual object, and its analysis can indicate driver  140  has fallen asleep as his eye leads have been closed for a period longer than a predefined threshold. 
     Device  120  can also receive data from a remote server indicating such as triangulation data indicative of its location and/or estimated speed. 
     Camera  122  can be used to estimate the distanced  472  between  120  and another object such as  130  of  FIG. 6 . Distance d can be estimated using the formula:
 
 d=S*W max I (2 W *tan( a/ 2)
         where:     474  a=the angular extent of a given scene that is imaged by camera  122 .   S=the known width of object such as object  130  in metric units     476  W=the width of object such as object  130  in pixel units   Wmax=the maximal width of an object in pixel units in camera  122         

       FIG. 5  is a flowchart of acts performed in accordance with an exemplary embodiment of the invention. 
     The acts serve the content matching needed in the embodiments described in figures such as  4 ,  6 ,  7 ,  8 ,  9 ,  10 ,  11   
     One of the inputs for the process is a visual object such as a photo frame captured by camera  122 . Others are for example sensors  124 , 126  input and other data as shown in  250  Processing can be performed on device  120  or on a remotes servers. 
     The following acts are performed, not necessarily in the below order: 
       509 —Receive location data such as GPS, AGPS, Cellular triangulation data and/or sensor  124 , 126  data such as acceleration, and camera  122 , 128  data and time. 
       511 —Use the above data to compute the speed in which  110  is traveling (both magnitude and direction in  3  axes. For example, two GPS points and in two time points give the average velocity. Speed can also be calculated using the camera data. Angular data from sensors data can give the estimated horizon point. The horizon can be calculated using the camera data as well. Other possible computations are:
         Tilt—both to the side (around Z axis) and to the front (around Y axis), calculated from the orientation sensor values.   Horizon Line—calculated from the tilt of the device around its Y axis and translated to pixel Y-coordinate according to the screen resolution.   Bearing line—though it can be calibrated manually by the user dragging the vertical bearing line. A few automatic methods are possible:
           Calculating the angle between the compass azimuth and the GPS-based bearing azimuth   Calculating the angle between the phone screen and the car&#39;s windshield based on the average forces working on the phone (from the accelerometer sensor)   Calculating the driving direction using pattern recognition of the street lane lines   
               

       512 —An object is detected, for example a car such as  130 . 
       514 —The object is classified to a category, for example a car, a motorcycle or a person. 
       516 —A specific object is identified, such as the car from previous frame, or a person called John Smith. 
       518 —Specific object attributes are extracted such as:
         Car color   Texture   Shape   License plate numbers   Hair color   Object dimension such car&#39;s width, persons height.       

       520 —object can be counted such as counting the number of cars on the road, or the number of shoppers  834  near store  832   
       522 —distance and or direction is calculated to the object such as:
         The distance from  122  as shown if  FIG. 4B     the direction to the object such as the angular direction   The relative speed from the object.   The time to collision with the object       

       524 —The risk of collision is calculated taking in account:
         The device  120 &#39;s speed using parameters such as GPS and devices sensors such as  124 .   Estimated time to collision   Road conditions   Car condition   Visibility   Drivers conditions such as estimated reaction time   Sensor information from  124 , 126         

     Device  120  or devices connected to it can than show to user such as driver 
       140  and/or other users in vehicle  110  information such as: 
       526 : object information such as any of the attributes described in  518   
       528 : warning such as driver warning or advice such a suggestion to change a lane using GIS info such as  1240  such as traffic flow information. 
       530 : advertisements such as sales in store  834 . Sometimes ads are local ads of businesses close to  120 . 
     The advertisements are optionally directed at inducing, promoting and/or encouraging purchase of products and/or services and/or acceptance of ideas. Optionally, the user to which the advertisements are displayed is not charged for display of the advertisements, but rather the provider of the advertisements is charged for their display. In some cases the advertisement is an audio sound such as a radio advertisement. Sometimes the advertisements are displayed only when device  120  indicates the car  110  is slow, in complete stop or in a traffic jam 
     Steps  512 ,  514 ,  516 ,  518  can all use Content analysis and content match. 
     Some of the steps  512 - 530  are optional. 
       FIG. 6  is a scheme describing a system and process in accordance with an exemplary embodiment of the invention. 
     Scheme shows a first, lead vehicle  130  traveling along a road  620  and followed by a second vehicle  110  having device  120 . 
     Driver  140  is driving the second vehicle  110 . System  490  processes images of the environment in front of the second vehicle  110  and produces information out of them. 
     Using this information system  490  calculates distance (d)  472  between two vehicles  110 , 130  and speed of second vehicle  110  at any given time as further described in  FIG. 5 . 
     According to these parameters system  490  then processes images taken by camera  122  and estimates the risk of collision between the two vehicles for example by comparing the estimated time to collision and the time to collision threshold. The risk to collision can take in account the breaking time, the cars relative distance, velocity, acceleration and jolt. Road conditions such as wet road (such as  826 ), oil spills, and the presence of other car, and drivers  140  expected reaction time due to his fatigue and his reaction time history. 
     If such an estimated risk crosses a predefined threshold and/or vehicle  110  speed exceeds permissible, system reaction will occur. 
     Optionally, system  490  can extract further attributes of vehicle  130 . such as a for sale sign  610 , vehicle  130 &#39;s car model, color, size, condition 
     If such a vehicle is identified, system  490  produces a relevant notice such as an alert for potential vehicles for sale within range. 
     These alerts are also accessible to all system&#39;s  490  users via web. 
     Optionally, system  490  creates a system reaction in case the distance between  110  and  130  and/or the estimated time to collision is below a certain threshold. 
     Alternatively,  130  is behind car  110  and system  490  creates a system reaction in case the distance between  110  and  130  and/or the estimated time to collision is below a certain threshold. The system reaction can be displayed on the back side such as through the back window  444  of  110  using a back window sign. 
       FIG. 7  is a scheme describing a system and process in accordance with an exemplary embodiment of the invention. 
     Person  140  drives his vehicle  110  having device  120 . He is supposed to drive in accordance with lane markings  600 . 
     Nevertheless, during driving, person  140  is falling asleep or not paying attention. 
     Consequently, vehicle driving direction  720  deviates beyond a certain threshold from the middle of the lane markings  730   
     And even crosses the left marking. 
     System  490  process images taken by camera  122  and recognizes using steps such as the ones described in  FIG. 5 , the deviation from the middle of the lane. If such a deviation crosses a predefined threshold system  490  reaction will occur. 
     Optionally, system  490  will use the input from camera  122  and/or microphone  124  to check whether the driver has used the left turn blinker  710  in which case no alert will be created. 
       FIG. 8  is a scheme describing a system and process in accordance with an exemplary embodiment of the invention. 
     Scheme shows a vehicle/taxi  110  traveling along a road  620 . 
     System  490  processes images taken by camera  122 , 128  of the environment in front of the taxi  110  having device  120 , and produces information and data regarding items within driving range, such as:
         People waiting for a taxi  812  optionally in a real time map   Pavement stone  818     Shops and businesses  834  and their relevant traction   Road conditions such as bump  822  or wet road  826     Traffic signs above the road level such as stop sign  816 , or on the road level such as zebra crossing  824     Landscape conditions such as blossoming field  814     Crowd  832 , and his emotions, using features such as smile recognition or by analyzing the sound of the crowd   Police cars, police man, traps, laser gun   Traffic lights color   Traffic jams   Low visibility   Traffic offenders and license plate recognition   Measure street cleanness level, Report is sent to municipalities.   Water leaks, report is sent.       

     System  490  uses OCR technology to read and interpret traffic signs above the road level, this is Relevant to driving abroad. For example, Driver  140  is driving in a foreign country. Traffic and 
     Information signs are written in a foreign language which he doesn&#39;t understand. System  490  will recognize signs above road level, translate and alert driver  140  regarding relevant information. 
     Another example is, taxi driving along a road. System  490  recognizes people at the side of the road raising their hand for a taxi, System  490  then produces relevant notice, available to all system&#39;s users via web. 
     Yet, Another example is a car is driving along a road, a person face is captured and is compared against a person DB, for example: 
     Celebrity Faces DB in which case a system reaction is created such as sending a message that the celebrity was seen on a certain location using twitter.com of Facebook.com. 
     Abducted children DB in which case a message will be sent to local police 
     A person category DB of police or soldier uniforms. 
       FIG. 9  is a scheme describing a system and process in accordance with an exemplary embodiment of the invention. 
     Person  140  drives his vehicle  110 . 
     He is driving towards a pedestrian  902  who is crossing the road. Person 
       140  is falling asleep or not paying attention to the road. 
     As a result he doesn&#39;t notice pedestrian  902  crossing the road. System  490  processes images taken by camera  122  and estimates distance from and/or the relative speed to pedestrian  902  and the estimated risk for an accident. If such a risk crosses a predefined threshold system reaction will occur. 
       FIG. 10  is a scheme describing a system and process in accordance with an exemplary embodiment of the invention. 
     Scheme shows a vehicle  110  having device  120  and traveling along a road 
       620 . Driver  140  is driving his vehicle  110  and is seeking for a parking spot. 
     System  490  processes images of the environment surrounding vehicle  110 , 
     and produces information out of them. 
     From this information system  490  identifies available parking spots and alerts driver  140  when one is detected  1002 . For example pavement stones marking an allowed parking place such as  1008  with that are not taken by cars such as  1006  and  1004  and with a length that is above a predefined length. 
     These alerts are also accessible to all system&#39;s  490  users within suitable range via web. 
     Driver  140  then reaches parking spot  1002 , between two parking vehicles  1004 ,  1006  and tries to park his vehicle  110 . 
     System  490  processes images taken by cameras  122 , 128  and accordingly calculates parking route  1012 , then system  490  reaction will occur in order to guide driver  140  into parking spot  1002 . 
       FIG. 11  is a scheme describing a system and process in accordance with an exemplary embodiment of the invention. 
     Scheme shows a vehicle  110  traveling along a road  620 . System  490  processes images of the environment in front of the vehicle  110  and recognizes whether it&#39;s a day or a night driving. In case of night driving system  490  checks whether vehicle lights  1102  are turned on. If lights  1102  are off, system  490  preforms a reaction. 
     Moreover, system  490  recognizes whether vehicle  110  has reached its destination  1104  using Micronavigation for example by comparing the input received by  120  to the known images of taken before on that coordinates. In case of destination arrival system produces relevant notice. Micronavigation can be also used to navigate person  236  to a specific shelf in store  834 . Or to assist a driver in navigation such as telling him to change lanes or take a turn. 
       FIG. 12  is a scheme describing a system and process in accordance with an exemplary embodiment of the invention. 
     Information is collected using the act described in  FIG. 5  using one or more systems such as  490  on one or more objects  1210 . Optionally for each object its category  514  and attributes  518  are extracted. Object of the same of similar coordinates and or attributes can be counted  1230  in order to analyze the data. Preparation  1230  is sometimes the preparation such as  1240 . 
     The reports of  1240  can be of several categories such as: GIS information reports, Summarized information and street view including business names, crowd and traffic. 
     Examples of such reports are shown in  1260 : 
     A report of vacant parking places: Multiple cars such as  110  are driving through the city as shown in  FIG. 13 , in case a car comes across a vacant parking place, that spot is reported back through a public network to create the report. 
     A report of places in the road that require fixing such as  822 , that can help the municipal authority fix them 
     A report on businesses on the street, their names and block numbers (using OCR), the amount of traffic that passes next to them such as  832 , the number of people inside or waiting outside of them. An the emotions of these people (using smile recognition and/or analyzing the sounds that crowd is making) 
     A report on the overall sentiment in certain city region 
     A report on the overall status of cars in a certain region such as their models, are they old or new, do they have mechanical problems, what is the level of pollution they are making. 
     A report on the status of plants in the city, how many green regions are three, how many of them need irrigation (using IR), how many of them are blossoming. 
     A map of the city: 
     Roads using road recognition (for example many asphalt roads are black) 
     Buildings, using building recognition. 
     Street number of each of them using OCR of the street signs 
     Traffic signs such as  816 , 824 ,  600  using content match to traffic sign DB, including changing signs such as LED signs 
     A real time map of the Temperature on different parts of a region, such as a city temperature map 
     A report on driver behavior, the data collected by device  120  using camera  122  and/or sensors  124 ,  126  such as: acceleration, speed, accidents, near accidents, collision warnings can all be collected to create a database of driver behavior. The specific driver can be identified using face recognition or by the identity of device  120 . The data can be used to evaluate the risk of the specific driver making an accident and an overall risk scoring can be computed for that driver. The result can be the estimated cost of the diver is insurance risk and/or gas consumption to be used by the driver and/or his company and/or insurer. 
     A reported on wanted cars, for example each car such as  110 ,  1310 , and 
       1320  carry system such as  490  using devices such as  120 . In case system  490  identify a license plate of a neighboring car such as  130 , it uses LPR to report the license plate to a remote server such as  1340 . The remote server compares the found license plate to a wanted car database such as stolen cars, fugitives, and people with unpaid debt. In case match is found a system reaction is created such as an SMS to the local police station. 
     A report of places of interest, for example places where vehicles or people tend to slow down or even stop (that could be measured using GPS, acceleration, or the camera) are considered places that create higher level of interest. 
       FIG. 13  is a scheme describing a system and process in accordance with an exemplary embodiment of the invention. 
     The System is comprised of: 
     A fleet of platform such as  200 , for example cars  110 ,  1310 ,  1320  where each of them carries devices such as  120 . Platforms are connected via a public network such as wireless Internet  1330  to a remote server  1340 . Servers processes the captured by  1302  such as shown in  FIG. 5  or step  1230 . Reports such as  1240 , 1260  are shown using devices such as  120  or on a remote terminal such as  1342 . 
       FIGS. 14A and 14B  are schemes describing a system and process in accordance with an exemplary embodiment of the invention. 
     Object A and its coordinates are captured  1450  and its coordinates are recorder using systems such as a GPS. The same steps are performed on object B 
       1452  and data on both objects is stored  1454  in a DB. 
     Person  236  is moving in direction  1410  and passes by object a marked  1422  requests system such as  120  to get to object B or its coordinates. Device  120  uses sensors such as  122 ,  128 ,  124 ,  126  to capture information on object  1422  as described in step  1456 . The Captured data on object  1422  is compared against the data in the DB of  1454  to search  1458  for a content match. In case content match is found with object A and using it coordinates navigation instructions are calculated  1460  using the coordinates of object B in relation to the coordinates of object A and displayed  1462  to person  236 . 
     The system and process can be used for example to navigate in place where GPS usage is not possible such as between stores in a shopping mole, between shelves in a supermarket, and to find ones car in a parking lot for finding the right door in a an office place. 
     The system can be used for Micronavigation, for example to identify in case someone is navigating in the wrong lane, or took the wrong turn. 
       FIG. 15  is a schematic illustration of an information display system  940 , in accordance with an exemplary embodiment of the invention. 
     System  940  comprises a device  120  with cameras  122 , 128  which acquires images, optionally a video stream of images. The images are provided to a content analysis unit  954  which identifies objects of interest in the images. Information on the identified objects and optionally their attributes is forwarded to an information selection unit  958  which determines accordingly what information is to be displayed on a display  956 , using any of the above described methods. 
     In an exemplary embodiment of the invention device  120  may monitor people, such as person  942 , standing near display  956  and select advertisements for display  956  according to attributes of the people. For example, advertisements directed to a child audience may be displayed when device  954  identifies a large percentage of children in the images acquired by device  120 . Alternatively to being directed at a location from which display  956  is viewed, camera  952  may view an entrance to a shop or other closed area in which display  956  displays advertisements or other information. The advertisements displayed are optionally selected according to the average profile of people entering the shop. 
     In some embodiments of the invention, the advertisements are selected responsive to behavior against rules identified in the images of device  120 . For example, when a camera monitoring a printer at a work place identifies misuse of the printer it may show on display  956  a warning and/or use instructions. 
     Device  120  is stationary, in some embodiments. In other embodiments of the invention, Device  120  is a portable camera, possibly mounted on a mobile communication terminal. In these embodiments, display  956  is optionally the display of the mobile terminal. Alternatively, display  956  is separate from the mobile terminal, which periodically transmits information selection instructions to the display. In some embodiments of the invention, Device  120  stores the selected information until the mobile terminal is connected to a base computer. Device  120  may also be mounted on home and/or office appliances, such as refrigerators. 
     In some embodiments of the invention, the images from device  120  are additionally provided to a monitoring station  950 . Thus, device  120  is used for two different tasks and the cost of camera hardware is reduced. In some embodiments of the invention, installation of system  940  is financed by the advertisements. 
     As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied thereon. 
     Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. 
     Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wire-line, optical fiber cable, RF, etc., or any suitable combination of the foregoing. 
     Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The program code may execute entirely on the user&#39;s computer, partly on the user&#39;s computer, as a stand-alone software package, partly on the user&#39;s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user&#39;s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). 
     Aspects of the present invention are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other 
     programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks. 
     The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     The aforementioned flowchart and diagrams illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. 
     In the above description, an embodiment is an example or implementation of the inventions. The various appearances of “one embodiment,” “an embodiment” or “some embodiments” do not necessarily all refer to the same embodiments. 
     Although various features of the invention may be described in the context of a single embodiment, the features may also be provided separately or in any suitable combination. Conversely, although the invention may be described herein in the context of separate embodiments for clarity, the invention may also be implemented in a single embodiment. 
     Reference in the specification to “some embodiments”, “an embodiment”, “one embodiment” or “other embodiments” means that a particular feature, structure, or characteristic described in connection with the embodiments is included in at least some embodiments, but not necessarily all embodiments, of the inventions. 
     It is to be understood that the phraseology and terminology employed herein is not to be construed as limiting and are for descriptive purpose only. 
     The principles and uses of the teachings of the present invention may be better understood with reference to the accompanying description, figures and examples. 
     It is to be understood that the details set forth herein do not construe a limitation to an application of the invention. 
     Furthermore, it is to be understood that the invention can be carried out or practiced in various ways and that the invention can be implemented in embodiments other than the ones outlined in the description above. 
     It is to be understood that the terms “including”, “comprising”, “consisting” and grammatical variants thereof do not preclude the addition of one or more components, features, steps, or integers or groups thereof and that the terms are to be construed as specifying components, features, steps or integers. 
     If the specification or claims refer to “an additional” element, that does not preclude there being more than one of the additional element. \ 
     It is to be understood that where the claims or specification refer to “a” or “an” element, such reference is not be construed that there is only one of that element. 
     It is to be understood that where the specification states that a component, feature, structure, or characteristic “may”, “might”, “can” or “could” be included, that particular component, feature, structure, or characteristic is not required to be included. 
     Where applicable, although state diagrams, flow diagrams or both may be used to describe embodiments, the invention is not limited to those diagrams or to the corresponding descriptions. For example, flow need not move through each illustrated box or state, or in exactly the same order as illustrated and described. 
     Methods of the present invention may be implemented by performing or completing manually, automatically, or a combination thereof, selected steps or tasks. 
     The descriptions, examples, methods and materials presented in the claims and the specification are not to be construed as limiting but rather as illustrative only. 
     Meanings of technical and scientific terms used herein are to be commonly understood as by one of ordinary skill in the art to which the invention belongs, unless otherwise defined. 
     The present invention may be implemented in the testing or practice with methods and materials equivalent or similar to those described herein. 
     Any publications, including patents, patent applications and articles, referenced or mentioned in this specification are herein incorporated in their entirety into the specification, to the same extent as if each individual publication was specifically and individually indicated to be incorporated herein. In addition, citation or identification of any reference in the description of some embodiments of the invention shall not be construed as an admission that such reference is available as prior art to the present invention. 
     While the invention has been described with respect to a limited number of embodiments, these should not be construed as limitations on the scope of the invention, but rather as exemplifications of some of the preferred embodiments. Other possible variations, modifications, and applications are also within the scope of the invention. Accordingly, the scope of the invention should not be limited by what has thus far been described, but by the appended claims and their legal equivalents.