APPARATUS, METHOD, AND COMPUTER READABLE MEDIUM FOR MONITORING A NUMBER OF PASSENGERS IN AN AUTOMOBILE

A monitor is utilized for installing inside an automobile to monitor a number of passengers in an automobile. The monitor includes an image capturing device, and a processing unit is connected to the image capturing device. The image capturing device successively captures a plurality of images in the automobile. The processing unit receives the images from the image capturing device to arrange an image sequence, wherein the processing unit includes an image dividing module, an image processing module, and a motion detecting module. The image dividing module divides each of the images into a plurality of recognition blocks, the image processing module compares the recognition blocks of consecutive images in the image sequence to acquire an image variance value, and the motion detecting module has a threshold value and determines the recognition blocks as a human-present condition when the image variance value surpasses the threshold value.

DETAILED DESCRIPTION OF THE INVENTION

The present invention of the monitor to monitor a number of passengers in an automobile will be described with drawings as below.

The terms “a” and “an” refer to one or to more than one (i.e., to at least one) of the grammatical object of the article.

Please refer toFIG. 1, which shows a block diagram of the monitor of the present invention.

The present invention provides a monitor100to monitor a number of passengers in an automobile. The monitor100comprises an image capturing device10, a processing unit20connected to the image capturing device10, and a wireless communication apparatus30connected to the processing unit20. The image capturing device10can be a camera to capture a two-dimensional image, or a depth camera which captures a depth parameter from the image. In the present embodiment, the image capturing device10can be a TwinCAM, or an active depth camera, which adds the depth degree as an auxiliary parameter.

The processing unit20is connected to the image capturing device10to receive a plurality of consecutive images appeared inside the automobile captured by the image capturing device10, and then arranges the images into an image sequence. The processing unit20mainly includes an image dividing module21, an image processing module22, a motion detecting module23, and a counter24. The image dividing module21divides each of the images into a plurality of recognition blocks40(as shown inFIG. 2). Wherein, the recognizable range of the recognition block40is set up by car's OEM (Original Equipment Manufacturing), ODM (Original Design Manufacturing), or is adjustable by the installer, or is automatically adjustable by the processing unit based on the environmental factors. For example, based on the depth parameter, the space can be divided into several blocks. However, the above disclosures are only for illustrating the equivalent arrangement of the invention, without any restrictions to the present invention.

The image processing module22compares the recognition blocks40of consecutive images in the image sequence to acquire an image variance value. The term “consecutive images” used herein refers to the different figures derived from the same image sequence. For example, if the number of the captured images are 12 images, the images to be compared can be the 1stand the 2ndimage, or the 1stand 12thimage; it does not restrict to choose the two adjacent images. Specifically, the comparing methods can be the background subtraction method, the adaptive background subtraction method, temporal difference method, etc.

The motion detecting module23has a threshold value, and the threshold value can be acquired from the conclusion of the large numbers of the statistic and experimental data. The threshold value is used for comparing with the image variance value. If one of the image variance value in a recognition block40surpasses the threshold value, then the motion detecting module23determines that the recognition block40has an moving objects and transmits a True value to the counter24. After the counter24receives the True value, it calculates the amount of the received True values and records the amount of the moving objects in the recognition block40, so that the number of people in the automobile is obtained.

The wireless communication device30is connected to the processing unit20. The protocol of the wireless communication device30can be established on the wireless communication system 3G, 4G, WiFi system, etc., to connect with a remote server. In an exemplary embodiment, the above mentioned wireless communication device30can be a portable mobile communication device, or the communication apparatus which is set in the automobile and is connected to the OBD (On-Board Diagnostics) in advance. In another exemplary embodiment, the present invention can be coordinated with a directional antenna which is set on or close to the high occupancy vehicle lane in a detecting distance. As the automobile passes the lane, the automobile receives a triggering signal radiated from the directional antenna and thereby starting the monitor100of the present invention to count the number of people in the automobile.

Please also refer toFIG. 2andFIG. 3, which show a usage state diagrams of the present invention.

In order to separate each space of the recognition blocks40to avoid the recognition blocks40being overlapped or disturbed by each other, the image capturing device10can be a TwinCam, or a depth camera to get the depth value of the image. Therefore, as the image capturing device10divides an image into recognition blocks40, the depth value can be used as an auxiliary reference. More particularly, each of the recognition blocks40has a depth reference range “d” and the image capturing device10can get the depth value of the image by the camera or an infrared rays receiver. Besides, this depth value can be identified if any objects exist inside the recognition block40before confirmation of the image motion.

Moreover, the present invention further includes a driver attention alarm50in order to detect the driver's attention when driving. Also, the driver attention alarm50includes another image capturing device51and an alarm device52which is connected to the image capturing device51. This capturing device51is installed in front of the driver in order to detect the driver's attention condition. More specifically, the image capturing device51includes a face-detecting function and an eye-closing detecting function. When the driver starts the automobile, the ODB system delivers an activating signal to the image capturing device51. At the meantime, the image capturing device51starts to make a record of the face image of the driver, and further records the number of winks and the angle of face turning based on the facial images. If the number of winks of the driver surpasses a first threshold value in a stipulated time, or the angle of face turning of the driver surpasses a second threshold value in a stipulated time, the alarm device52makes a warning sound to alert the driver.

Please also refer toFIG. 4andFIG. 5, which show the diagrams of the method for monitoring a number of passengers in an automobile of the present invention.

The present invention provides a monitoring method to monitor the number of passengers in the automobile. The method comprises the following steps: at the beginning, when users start the engine, the ODB system delivers an activating signal to the processing unit20so that the processing unit20gets the information that the engine is under the starting status. Therefore, the processing unit20starts the image capturing device10(also, the image capturing device10can be started by external conditions) and the image capturing device10successively captures a plurality of images in the automobile. The processing unit20then arranges the images into an image sequence (step S100). Then, each image in the image sequence is divided into a plurality of recognition blocks40through a image-dividing module21(step S110). When images are divided into a plurality of recognition blocks40, the variance value of each recognition block is calculated so that the number of persons in the recognition blocks40can be known (step S120). Please refer toFIG. 5, which illustrates the detailed steps on how to identify whether there has person present in the recognition block. First, the capturing device concurrently measures the depths of the recognition blocks to detect whether there are any objects within the depth reference range “d” (step S121). If no objects present in the depth reference range “d”, then no person present in the recognition block is determined (step S125). However, if there are objects in the the depth reference range “d”, then the subsequent step is conducted. It should be noted that the depth measure range is set in advance, so that this step can be operated before or after the image-dividing step). Further, the image-processing module22compares the recognition block40of consecutive images in the image sequence and acquires an image variance value (step S122). The motion-detecting module23compares the image variance value with a threshold value (step S123). If the image variance value surpasses the threshold value, it is concluded that there are people present in the recognition block40and a True value is also generated and is transmitted to the counter24(step S124). Otherwise, if the image variance value is under the threshold value, it is concluded that there has no people present in the recognition block40(step S125). Finally, the counter24calculates the number of passengers in the automobile based on the received True value. If the number of passengers fails to reach a regulated number (usually 2 people) (step S130), the counter transmits a warning to a remote server (step S140). On the other hand, if the passenger numbers surpass the regulated number, then the detecting loop is ended.

In order to understand the equivalent range of the variance value of images of the present invention, several implementing ways are proposed for detecting motion change of the images.

The following is first embodiment.

Please also refer toFIG. 6, which shows the algorithm flow chart of the first embodiment. As the flow chart shows, the image-processing module obtains the background image of each recognition block40first, and saves the background image as a reference image. The image processing module22gets the image sequences, which are already divided by an image-dividing process. Then, through a differential process, the image processing module22removes the background image of the recognition block40(step S1221) and the background removed consecutive images respectively include a pixel matrix. The step is followed by a differential process to the pixel matrix of two consecutive images to acquire the difference value matrixes (step S1222). Subsequently, an image variance value is obtained based on the proportion between the difference value matrix and the recognition block's40image or based on the sum of an absolute values of each difference value of the difference value matrixes (step S1223). The image variance value is compared with a threshold value (step S1231). If the image variance value surpasses the threshold value, the recognition block is judged as human present, and a True value is transmitted to the counter24(step S124).

In the present embodiment, the above mentioned differential process is a subtraction between gray values of the consecutive images of the same position, or a vector distance of the chromaticity coordinate between the two consecutive pixels of the same position. Since there are several reference values available, the present invention is not limited to any certain types. Moreover, it shall be noted that in the present embodiment, the background removing process is not an essential step.

The second embodiment is illustrated as follows.

Please also refer toFIG. 7, which shows the algorithm flow chart of the second embodiment of the present invention. As the flow chart shows, the image coordinates in the trait block is acquired based on the trait of human bodies. First, the image processing module22obtains the background image of each recognition block40and saves the background image as a reference image. Then, the image processing module22obtains the image sequences that are already divided by image dividing process, and a differential process is conducted to the image of the recognition block40and the background image respectively to complete background removing (step S1224). After background removing, the image processing module22conduct a image binarization process in order to get the border of the image. The image processing module then obtains a trait block that is presented in each of the images (i.e., the trait block is a block having a much bigger distinct from the surrounding images) (step S1225). Then, the coordinate position of the center of the trait block in the recognition block40is recorded, and a bias vector of the center of the trait block in consecutive images is obtained (which is equal to the image variance value) (step S1226). Subsequently, the distance of bias vector is compared to the threshold value. If the distance of bias vector surpasses the threshold value, the recognition block is judged as human present, and a True value is transmitted to the counter24(step S124).

The above examples are only regarded as parts of embodiment for reference. In the present invention, the comparison method shall not be limited to the above mentioned two embodiments.

In addition, the method of the present invention is able to be programmed into a software program that can be saved in a computer readable recording medium such as a Disc, a hard disc, or a semiconductor memory device and the computer-readable recording medium is accessible and is executed on an electronic device which is able to read the computer-readable recording medium. In particularly, the electronic devices is a small portable electronic device, an EDR (event data recorder), a driving security assisting device, an ODB system of vehicle, or the computer equipment and the like.

In conclusion, the present invention detects the number of passengers in the automobiles via the image capturing device. During the high occupancy vehicle control, the control center remotely monitor the passenger number by the image capturing device in the automobile and thereby avoiding the inconvenience of controlling passenger numbers by labor. Besides, uses a depth camera to detect whether there are objects within the depth reference range in advance, thereby improving the detecting accuracy. Furthermore, the present invention can further include an OBD or wireless communication system so that the monitor of the present invention is started when the vehicle is started, going on a highway, or into a HOV lane, thereby achieving effective monitoring.