Patent Publication Number: US-10769475-B2

Title: Method of identifying objects based on region of interest and electronic device supporting the same

Description:
CROSS-REFERENCE TO RELATED APPLICATION AND CLAIM OF PRIORITY 
     This application is based on and claims priority under 35 U.S.C. § 119 to Korean Patent Application No. 10-2017-0106133 filed on Aug. 22, 2017 in the Korean Intellectual Property Office, the disclosure of which is incorporated by reference herein in its entirety. 
     BACKGROUND 
     1. Field 
     The present invention relates to a method of identifying objects based on a region of interest (ROI) and an electronic device supporting the method. 
     2. Description of Related Art 
     Advances in information, communication, and semiconductor technologies have enabled popularization of electronic devices. Electronic devices have evolved into convergence devices supporting heterogeneous functions having originated from distinct fields. For example, such an electronic device may provide a function for identifying an object in the obtained content. 
     For object identification in a video, the electronic device may use a technique of comparing successive frames of the video and separating the moving object region from the background region. 
     For object identification in a still image, after the electronic device separates similar regions based on the color, the user may have to select a region corresponding to the object or draw a closed curve on the outline of the object. 
     Recently, a technique of converting the most conspicuous region in a still image into a saliency map has been used for object identification. 
     However, such a user-input based technique of object identification may be highly affected by the sophistication of the user input and may also require excessive interaction with the user. In the case of a saliency map technique, the object desired by the user may be not correctly identified, and the outline information of the object may be not accurately reflected. 
     SUMMARY 
     The present invention has been made in view of the above problems. Accordingly, an aspect of the present invention is to provide an object identification method based on the region of interest and an electronic device supporting the method. 
     In accordance with an aspect of the present invention, an electronic device is provided. The electronic device may include: a display; and a processor functionally connected with the display. The processor may be configured to: output content including one or more objects through the display; receive user input for specifying at least one point in the entire region of the content; determine a portion of the entire region with respect to the at least one point as a search region; obtain a saliency map associated with the content based on the search region; and determine the region of interest of the user based on the saliency map. 
     In accordance with another aspect of the present invention, there is provided a method for object identification based on the region of interest. The method may include: outputting content including one or more objects through a display; receiving user input for specifying at least one point in the entire region of the content; determining a portion of the entire region with respect to the at least one point as a search region; obtaining a saliency map associated with the content based on the search region; and determining the region of interest of the user based on the saliency map. 
     In a feature of the present invention, the electronic device can accurately identify an object desired by the user through a simple user input, and can provide a user interface to intuitively confirm the region of interest of the user. 
     Before undertaking the DETAILED DESCRIPTION below, it may be advantageous to set forth definitions of certain words and phrases used throughout this patent document: the terms “include” and “comprise,” as well as derivatives thereof, mean inclusion without limitation; the term “or,” is inclusive, meaning and/or; the phrases “associated with” and “associated therewith,” as well as derivatives thereof, may mean to include, be included within, interconnect with, contain, be contained within, connect to or with, couple to or with, be communicable with, cooperate with, interleave, juxtapose, be proximate to, be bound to or with, have, have a property of, or the like; and the term “controller” means any device, system or part thereof that controls at least one operation, such a device may be implemented in hardware, firmware or software, or some combination of at least two of the same. It should be noted that the functionality associated with any particular controller may be centralized or distributed, whether locally or remotely. 
     Moreover, various functions described below can be implemented or supported by one or more computer programs, each of which is formed from computer readable program code and embodied in a computer readable medium. The terms “application” and “program” refer to one or more computer programs, software components, sets of instructions, procedures, functions, objects, classes, instances, related data, or a portion thereof adapted for implementation in a suitable computer readable program code. The phrase “computer readable program code” includes any type of computer code, including source code, object code, and executable code. The phrase “computer readable medium” includes any type of medium capable of being accessed by a computer, such as read only memory (ROM), random access memory (RAM), a hard disk drive, a compact disc (CD), a digital video disc (DVD), or any other type of memory. A “non-transitory” computer readable medium excludes wired, wireless, optical, or other communication links that transport transitory electrical or other signals. A non-transitory computer readable medium includes media where data can be permanently stored and media where data can be stored and later overwritten, such as a rewritable optical disc or an erasable memory device. 
     Definitions for certain words and phrases are provided throughout this patent document, those of ordinary skill in the art should understand that in many, if not most instances, such definitions apply to prior, as well as future uses of such defined words and phrases. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       For a more complete understanding of the present disclosure and its advantages, reference is now made to the following description taken in conjunction with the accompanying drawings, in which like reference numerals represent like parts: 
         FIG. 1  illustrates a network environment including electronic devices capable of configuring a region of interest for object identification according to various embodiments. 
         FIG. 2  illustrates a block diagram of the processor of an electronic device according to various embodiments. 
         FIG. 3  is a flowchart illustrating an object identification method according to various embodiments. 
         FIGS. 4A to 4F  illustrate an example of object identification. 
         FIG. 5  is a flowchart illustrating a case where a region of interest is provided before user input. 
         FIG. 6  illustrates an example of a region of interest provided in advance. 
         FIGS. 7A to 7C  illustrate an example of object identification when user input is received within the region of interest provided in advance. 
         FIGS. 8A to 8C  illustrate an example of object identification when user input is received outside the region of interest provided in advance. 
     
    
    
     DETAILED DESCRIPTION 
       FIGS. 1 through 8C , discussed below, and the various embodiments used to describe the principles of the present disclosure in this patent document are by way of illustration only and should not be construed in any way to limit the scope of the disclosure. Those skilled in the art will understand that the principles of the present disclosure may be implemented in any suitably arranged system or device. 
       FIG. 1  is a block diagram illustrating an electronic device  101  in a network environment  100  according to various embodiments. Referring to  FIG. 1 , the electronic device  101  in the network environment  100  may communicate with an electronic device  102  via a first network  198  (e.g., a short-range wireless communication network), or an electronic device  104  or a server  108  via a second network  199  (e.g., a long-range wireless communication network). According to an embodiment, the electronic device  101  may communicate with the electronic device  104  via the server  108 . According to an embodiment, the electronic device  101  may include a processor  120 , memory  130 , an input device  150 , a sound output device  155 , a display device  160 , an audio module  170 , a sensor module  176 , an interface  177 , a haptic module  179 , a camera module  180 , a power management module  188 , a battery  189 , a communication module  190 , a subscriber identification module (SIM)  196 , or an antenna module  197 . In some embodiments, at least one (e.g., the display device  160  or the camera module  180 ) of the components may be omitted from the electronic device  101 , or one or more other components may be added in the electronic device  101 . In some embodiments, some of the components may be implemented as single integrated circuitry. For example, the sensor module  176  (e.g., a fingerprint sensor, an iris sensor, or an illuminance sensor) may be implemented as embedded in the display device  160  (e.g., a display). 
     The processor  120  may execute, for example, software (e.g., a program  140 ) to control at least one other component (e.g., a hardware or software component) of the electronic device  101  coupled with the processor  120 , and may perform various data processing or computation. According to one embodiment, as at least part of the data processing or computation, the processor  120  may load a command or data received from another component (e.g., the sensor module  176  or the communication module  190 ) in volatile memory  132 , process the command or the data stored in the volatile memory  132 , and store resulting data in non-volatile memory  134 . According to an embodiment, the processor  120  may include a main processor  121  (e.g., a central processing unit (CPU) or an application processor (AP)), and an auxiliary processor  123  (e.g., a graphics processing unit (GPU), an image signal processor (ISP), a sensor hub processor, or a communication processor (CP)) that is operable independently from, or in conjunction with, the main processor  121 . Additionally or alternatively, the auxiliary processor  123  may be adapted to consume less power than the main processor  121 , or to be specific to a specified function. The auxiliary processor  123  may be implemented as separate from, or as part of the main processor  121 . 
     The auxiliary processor  123  may control at least some of functions or states related to at least one component (e.g., the display device  160 , the sensor module  176 , or the communication module  190 ) among the components of the electronic device  101 , instead of the main processor  121  while the main processor  121  is in an inactive (e.g., sleep) state, or together with the main processor  121  while the main processor  121  is in an active state (e.g., executing an application). According to an embodiment, the auxiliary processor  123  (e.g., an image signal processor or a communication processor) may be implemented as part of another component (e.g., the camera module  180  or the communication module  190 ) functionally related to the auxiliary processor  123 . 
     The memory  130  may store various data used by at least one component (e.g., the processor  120  or the sensor module  176 ) of the electronic device  101 . The various data may include, for example, software (e.g., the program  140 ) and input data or output data for a command related thereto. The memory  130  may include the volatile memory  132  or the non-volatile memory  134 . 
     The program  140  may be stored in the memory  130  as software, and may include, for example, an operating system (OS)  142 , middleware  144 , or an application  146 . 
     The input device  150  may receive a command or data to be used by other component (e.g., the processor  120 ) of the electronic device  101 , from the outside (e.g., a user) of the electronic device  101 . The input device  150  may include, for example, a microphone, a mouse, or a keyboard. 
     The sound output device  155  may output sound signals to the outside of the electronic device  101 . The sound output device  155  may include, for example, a speaker or a receiver. The speaker may be used for general purposes, such as playing multimedia or playing record, and the receiver may be used for an incoming calls. According to an embodiment, the receiver may be implemented as separate from, or as part of the speaker. 
     The display device  160  may visually provide information to the outside (e.g., a user) of the electronic device  101 . The display device  160  may include, for example, a display, a hologram device, or a projector and control circuitry to control a corresponding one of the display, hologram device, and projector. According to an embodiment, the display device  160  may include touch circuitry adapted to detect a touch, or sensor circuitry (e.g., a pressure sensor) adapted to measure the intensity of force incurred by the touch. 
     The audio module  170  may convert a sound into an electrical signal and vice versa. According to an embodiment, the audio module  170  may obtain the sound via the input device  150 , or output the sound via the sound output device  155  or a headphone of an external electronic device (e.g., an electronic device  102 ) directly (e.g., wiredly) or wirelessly coupled with the electronic device  101 . 
     The sensor module  176  may detect an operational state (e.g., power or temperature) of the electronic device  101  or an environmental state (e.g., a state of a user) external to the electronic device  101 , and then generate an electrical signal or data value corresponding to the detected state. According to an embodiment, the sensor module  176  may include, for example, a gesture sensor, a gyro sensor, an atmospheric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an infrared (IR) sensor, a biometric sensor, a temperature sensor, a humidity sensor, or an illuminance sensor. 
     The interface  177  may support one or more specified protocols to be used for the electronic device  101  to be coupled with the external electronic device (e.g., the electronic device  102 ) directly (e.g., wiredly) or wirelessly. According to an embodiment, the interface  177  may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, a secure digital (SD) card interface, or an audio interface. 
     A connecting terminal  178  may include a connector via which the electronic device  101  may be physically connected with the external electronic device (e.g., the electronic device  102 ). According to an embodiment, the connecting terminal  178  may include, for example, a HDMI connector, a USB connector, a SD card connector, or an audio connector (e.g., a headphone connector), 
     The haptic module  179  may convert an electrical signal into a mechanical stimulus (e.g., a vibration or a movement) or electrical stimulus which may be recognized by a user via his tactile sensation or kinesthetic sensation. According to an embodiment, the haptic module  179  may include, for example, a motor, a piezoelectric element, or an electric stimulator. 
     The camera module  180  may capture a still image or moving images. According to an embodiment, the camera module  180  may include one or more lenses, image sensors, image signal processors, or flashes. 
     The power management module  188  may manage power supplied to the electronic device  101 . According to one embodiment, the power management module  188  may be implemented as at least part of, for example, a power management integrated circuit (PMIC). 
     The battery  189  may supply power to at least one component of the electronic device  101 . According to an embodiment, the battery  189  may include, for example, a primary cell which is not rechargeable, a secondary cell which is rechargeable, or a fuel cell. 
     The communication module  190  may support establishing a direct (e.g., wired) communication channel or a wireless communication channel between the electronic device  101  and the external electronic device (e.g., the electronic device  102 , the electronic device  104 , or the server  108 ) and performing communication via the established communication channel. The communication module  190  may include one or more communication processors that are operable independently from the processor  120  (e.g., the application processor (AP)) and supports a direct (e.g., wired) communication or a wireless communication. According to an embodiment, the communication module  190  may include a wireless communication module  192  (e.g., a cellular communication module, a short-range wireless communication module, or a global navigation satellite system (GNSS) communication module) or a wired communication module  194  (e.g., a local area network (LAN) communication module or a power line communication (PLC) module). A corresponding one of these communication modules may communicate with the external electronic device via the first network  198  (e.g., a short-range communication network, such as BLUETOOTH, wireless-fidelity (WI-FI) direct, or infrared data association (IRDA)) or the second network  199  (e.g., a long-range communication network, such as a cellular network, the Internet, or a computer network (e.g., LAN or wide area network (WAN)). These various types of communication modules may be implemented as a single component (e.g., a single chip), or may be implemented as multi components (e.g., multi chips) separate from each other. The wireless communication module  192  may identify and authenticate the electronic device  101  in a communication network, such as the first network  198  or the second network  199 , using subscriber information (e.g., international mobile subscriber identity (IMSI)) stored in the subscriber identification module  196 . 
     The antenna module  197  may transmit or receive a signal or power to or from the outside (e.g., the external electronic device) of the electronic device  101 . According to an embodiment, the antenna module  197  may include one or more antennas, and, therefrom, at least one antenna appropriate for a communication scheme used in the communication network, such as the first network  198  or the second network  199 , may be selected, for example, by the communication module  190  (e.g., the wireless communication module  192 ). The signal or the power may then be transmitted or received between the communication module  190  and the external electronic device via the selected at least one antenna. 
     At least some of the above-described components may be coupled mutually and communicate signals (e.g., commands or data) therebetween via an inter-peripheral communication scheme (e.g., a bus, general purpose input and output (GPIO), serial peripheral interface (SPI), or mobile industry processor interface (MIPI)). 
     According to an embodiment, commands or data may be transmitted or received between the electronic device  101  and the external electronic device  104  via the server  108  coupled with the second network  199 . Each of the electronic devices  102  and  104  may be a device of a same type as, or a different type, from the electronic device  101 . According to an embodiment, all or some of operations to be executed at the electronic device  101  may be executed at one or more of the external electronic devices  102 ,  104 , or  108 . For example, if the electronic device  101  should perform a function or a service automatically, or in response to a request from a user or another device, the electronic device  101 , instead of, or in addition to, executing the function or the service, may request the one or more external electronic devices to perform at least part of the function or the service. The one or more external electronic devices receiving the request may perform the at least part of the function or the service requested, or an additional function or an additional service related to the request, and transfer an outcome of the performing to the electronic device  101 . The electronic device  101  may provide the outcome, with or without further processing of the outcome, as at least part of a reply to the request. To that end, a cloud computing, distributed computing, or client-server computing technology may be used, for example. 
       FIG. 2  is a block diagram of the processor of an electronic device according to various embodiments. 
     In various embodiments, the processor  120  may include a search region determiner  210 , a main region detector  220 , a region divider  230 , and a region-of-interest determiner  240 . In  FIG. 2 , the search region determiner  210 , the main region detector  220 , the region divider  230 , and the region-of-interest determiner  240  are shown as being included in a single processor. However, the search region determiner  210 , the main region detector  220 , the region divider  230 , and the region-of-interest determiner  240  may belong to separate processors. 
     In one embodiment, the search region determiner  210  may determine a portion of the entire region of the content as a search region with respect to at least one point specified by the user. Specifically, the search region determiner  210  can examine relative variations between blocks composed of one or more pixels constituting the content and obtain an entropy map related to the content based on the relative variations. When the entropy map is obtained, the search region determiner  210  can divide the entropy map according to a specific criterion. The search region determiner  210  may identify at least one region to which the point specified by the user belongs among the divided regions and calculate the statistical characteristics of the identified region. The search region determiner  210  may identify additional regions having statistical characteristics similar to those of the identified region. Then, the search region determiner  210  may determine a search region that is composed of the at least one region to which the point specified by the user belongs and the additional regions having similar statistical characteristics. 
     In one embodiment, the main region detector  220  can obtain a saliency map related to the content on the basis of the search region. For example, the main region detector  220  can obtain a saliency map reflecting main regions by applying a machine-learning algorithm, a deep-learning algorithm, or an image processing algorithm to the search region. As another example, the main region detector  220  can obtain a weighted saliency map by assigning different weights to at least a portion of the saliency map based on the point specified by the user. 
     In one embodiment, the region divider  230  may obtain an index map related to the content by dividing the entire region of the content into similar regions based on a preset criterion. For example, the region divider  230  may apply a super-pixel algorithm to the content to divide the content into regions having the same or similar color. Then, the region divider  230  may obtain an index map related to the content by assigning an index to each of the divided regions. 
     In one embodiment, the region-of-interest determiner  240  may determine the region of interest (ROI) of the user on the basis of the saliency map obtained from the search region determined based on the entropy map, and the index map obtained based on the entire region of the content. The region-of-interest determiner  240  can identify an object by overlapping, e.g., the saliency map (or weighted saliency map) and the index map. For example, it is possible to identify the object corresponding to the point specified by the user by examining the size of the main region in the saliency map in consideration of the index map associated with the divided similar regions. Thereafter, the region-of-interest determiner  240  may determine the region of interest including the identified object, and draw an outline of the determined region of interest and output it through the display. 
     According to various embodiments of the present invention, the electronic device (e.g., electronic device  101  in  FIG. 1 ) may include a display (e.g., display device  160  in  FIG. 1 ) and a processor (e.g., processor  120  in  FIG. 1 ) functionally connected with the display. The processor may be configured to: output content including one or more objects through the display; receive user input for specifying at least one point in the entire region of the content; determine a portion of the entire region as a search region with respect to the at least one point; obtain a saliency map related to the content based on the search region; and determine a region of interest of the user based on the saliency map. 
     In one embodiment, the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may be configured to obtain an index map related to the content by dividing the entire region of the content into similar regions based on preset criteria. The region of interest of the user may be determined based on the saliency map and the index map. 
     In one embodiment, the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may be configured to examine relative variations between blocks composed of one or more pixels constituting the content, and obtain an entropy map related to the content based on the relative variations. 
     In one embodiment, the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may be configured to: divide the entropy map according to a specific criterion; identify at least one region to which the point specified by the user belongs; calculate the statistical characteristics of the identified region; find additional regions having statistical characteristics similar to those of the identified region; and determine the search region as including the identified region and the found additional regions. 
     In one embodiment, the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may be configured to generate a weighting matrix based on the point specified by the user, and obtain a weighted saliency map by applying the weighting matrix to at least a portion of the saliency map. 
     In one embodiment, in the electronic device (e.g., electronic device  101  in  FIG. 1 ), the preset criteria may include at least one of color, outline, and contrast. 
     In one embodiment, the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may be configured to identify an object according to the point specified by the user by overlapping main regions in the saliency map and similar regions in the index map. 
     In one embodiment, the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may be configured to: provide a main region of the content as a preset region of interest; and determine, if a user input is received within the preset region of interest, the region other than the preset region of interest as a non-search region. 
     In one embodiment, the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may be configured to: provide a main region of the content as a preset of interest; and determine, if a user input is not received within the preset region of interest, at least a portion of the content including the preset region of interest as a non-search region. 
     In one embodiment, the electronic device (e.g., electronic device  101  in  FIG. 1 ) may receive the user input by utilizing at least one of touch input using a portion of the human body (e.g., the user&#39;s body) or a pen, hovering input using a portion of the human body or a pen, and non-contact recognition. 
       FIG. 3  is a flowchart of an object identification method according to various embodiments. 
     With reference to  FIG. 3 , at operation  310 , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may output content including one or more objects through the display (e.g., display device  160  in  FIG. 1 ). 
     In various embodiments, the content may include various digital information such as images and videos. The content may include various types of information that the electronic device can output on the screen, such as images like pictures or photographs, preview images captured by the camera, and text data. An object can refer to anything distinct from the background in the content. 
     At operation  320 , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may receive user input for specifying at least one point in the entire region of the content. 
     In various embodiments, the user input may include various ways of specifying at least one point in the content. The user input may be an input for specifying at least one point using an input means. When the display includes a touch panel, the user input may be a touch input for specifying at least one point using a portion of the human body (e.g., finger) or a pen. At least one point can be specified via a hovering input using a pen or a portion of the body (e.g., finger). The processor of the electronic device may specify at least one point using at least one of the non-contact recognition functions. For example, the processor can specify at least one point by recognizing the face, eye, iris, hand motion, or voice of the user through a camera or a microphone. 
     In various embodiments, the user may specify a plurality of points. In the description, it is assumed that the user specifies one point. When the user specifies a plurality of points, the processor can identify a plurality of objects corresponding respectively to the plurality of points specified by the user. 
     At operation  330 , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may determine a portion of the entire region as a search region with respect to the at least one point. 
     In the case where the content includes a plurality of objects, it may be unnecessary to identify an object other than the object selected by the user. If the entire region of the content is set as the search region, an object not selected by the user may be identified. As a result, the outline information of the objects may be not accurately reflected. To identify an object corresponding to at least one point specified by the user, the processor may limit the area in which the object is to be searched to a portion of the entire region of the content. 
     In various embodiments, the processor can predict the region in which the object selected by the user can exist among the entire region of the content to determine the search region. Specifically, the processor (e.g., processor  120  in  FIG. 1  or search region determiner  210  in  FIG. 2 ) may examine relative variations between adjacent pixels or adjacent blocks on the basis of the information contained in pixels constituting the content or blocks including multiple pixels, and obtain an entropy map related to the content based on the relative variations between the pixels or blocks. In one embodiment, the processor may obtain an entropy map by applying the relative variations between the adjacent pixels or blocks in sequence to the content with respect to the pixel or block corresponding to the point specified by the user. 
     Upon obtaining the entropy map, the processor can divide the entropy map according to a given criterion. For example, the processor may divide the entropy map in various units such as 5×5 or 3×3 units. The processor may identify at least one region to which the point specified by the user belongs among the divided regions and calculate the statistical characteristics of the identified region. Then, the processor may find additional regions having statistical characteristics similar to those of the identified region. 
     The processor may determine the search region as including the region to which the point specified by the user belongs and the additional regions having statistical characteristics similar to those thereof. Here, the search region may be formed in one shape including at least one region to which the point specified by the user belongs. For example, if there is a region that exists separately among the regions having similar statistical characteristics, that region can be excluded from the search region. 
     Upon determining the search region, at operation  340 , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may obtain a saliency map related to the content based on the search region. 
     In various embodiments, the processor may obtain a saliency map indicating a main region within the search region. The processor (e.g., processor  120  in  FIG. 1  or main region detector  220  in  FIG. 2 ) can obtain a saliency map reflecting main regions by applying, for example, a machine-learning algorithm, a deep-learning algorithm, or an image processing algorithm to the search region. The main region may refer to a region occupied by the objects in the search region. For example, the main region can be identified by assigning a saliency value to each pixel and aggregating those pixels having a saliency value equal to or greater than a preset threshold. 
     In various embodiments, the processor may assign different weights to a portion of the saliency map based on the point specified by the user. For example, the processor may generate a weighting matrix that assigns a high weight to the point specified by the user and assigns a low weight to a point far from the point specified by the user. The processor may generate a weighted saliency map by applying the weighting matrix to a portion of the saliency map. The weighted feature map may cause the object corresponding to the point specified by the user to be reflected in the main region. 
     At operation  350 , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may determine whether to obtain an index map associated with the content. 
     In various embodiments, the processor (e.g., processor  120  in  FIG. 1 , or region divider  230  in  FIG. 2 ) may divide the entire region of the content into similar regions based on a preset criterion. The processor may analyze the content in terms of color, outline, or contrast to divide the content into similar regions. The processor may apply a super-pixel algorithm to the content to divide the content into regions having the same or similar color. Then, the processor may obtain an index map related to the content by assigning an index to each of the divided regions. 
     In one embodiment, the operation of obtaining the index map can be omitted. For example, if an object in the content is clearly distinguished from the background, the object can be identified without use of the index map. As another example, in the case of a preview image of a camera, an object can be identified without obtaining an index map in consideration of processing speed and current consumption. Hence, the processor may determine whether to obtain an index map associated with the content, and may perform operation  360  or operation  370  based on the determination result. 
     In the above description, operation  350  is described as being executed after operation  330 . However, the electronic device may simultaneously execute operation  330  and operation  350  using a single processor or two or more processors. 
     Upon determining not to obtain an index map associated with the content, at operation  360 , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may determine the region of interest of the user on the basis of the saliency map. For example, the region corresponding to the main region in the saliency map can be determined as the region of interest of the user. 
     Upon determining to obtain an index map associated with the content, at operation  370 , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may determine the region of interest of the user on the basis of the saliency map and the index map. 
     In various embodiments, the processor (e.g., processor  120  in  FIG. 1 , or region-of-interest determiner  240  in  FIG. 2 ) can identify an object by overlapping the saliency map (or weighted saliency map) and the index map. For example, the processor can determine whether a similar region in the index map overlapping the main region in the saliency map constitutes the whole or a part of an object. If there are multiple similar regions constituting a part of the object, such similar regions can be identified in aggregate as one object. The saliency map may fail to accurately reflect the outline information of the object, and the index map may fail to accurately reflect the shape and position information of the object. Hence, it is possible to relatively accurately identify the object selected by the user by utilizing the saliency map and the index map in a complementary way. 
     In various embodiments, after identifying the object, the processor may determine the region of interest of the user including the identified object. For example, as an object can have an arbitrary shape, the processor can determine the region of interest including the identified object. The processor may display the region of interest on the display so that the user can intuitively recognize the region of interest. For example, the processor may draw an outline of the region of interest and output it through the display. 
       FIGS. 4A to 4F  illustrate an example of object identification. 
     With reference to  FIG. 4A , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may output content  401  including one or more objects through the display (e.g., display device  160  in  FIG. 1 ). For example, the content  401  may include a first object  411 , a second object  412 , a third object  413 , a fourth object  414 , and a fifth object  415 . To select the first object  411 , the user may touch or hover over one point  421  of the region forming the first object  411  with the pen  420  or a finger. Alternatively, the user may specify one point  421  of the region forming the first object  411  using one of non-contact recognition functions. 
     With reference to  FIG. 4B , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may determine a portion of the entire region of the content  401  as a search region with respect to the point  421  specified by the user. For example, the electronic device may obtain an entropy map associated with the content  401  and divide the entropy map according to a certain criterion.  FIG. 4B  shows an example in which the entropy map is divided into 5×5 units, but the present invention is not limited thereto. The electronic device may identify at least one region  430  to which the point specified by the user belongs among the divided regions and calculate the statistical characteristics of the identified region  430 . The electronic device may find additional regions  441  having statistical characteristics similar to those of the identified region  430 . Then, the electronic device may determine the search region as including the region  430  to which the point specified by the user belongs and the additional regions  441  having statistical characteristics similar to those thereof. In  FIG. 4B , the divided entropy map is displayed on the screen for ease of description, but the entropy map may be not displayed on the screen. 
     With reference to  FIG. 4C , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may obtain a saliency map related to the content  401  based on the search region including additional regions  441 . For example, as shown in part (a) of  FIG. 4C , the electronic device may obtain a saliency map reflecting the main region  450  based on the determined search region. Alternatively, the electronic device may generate a weighted saliency map by applying a weighting matrix to a portion of the saliency map. Thereafter, as shown in part (b) of  FIG. 4C , the processor may combine the non-search region  442  excluded from the search region with the saliency map obtained in part (c) of  FIG. 4C  to obtain a saliency map having the same size as the entire content. In  FIG. 4C , the saliency map is displayed on the screen for ease of description, but the saliency map may be not displayed on the screen. 
     With reference to  FIG. 4D , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may divide the content into similar regions based on a preset criterion to obtain an index map associated with the content. For example, the electronic device may analyze the entire region of the content in terms of color, outline, or contrast and obtain an index map associated with the content by dividing the content into similar regions. In  FIG. 4D , the index map is displayed on the screen for ease of description, but the index map may be not displayed on the screen. 
     With reference to  FIG. 4E , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may identify the object on the basis of the saliency map and the index map. For example, the processor can identify the object by overlapping the saliency map and the index map. Specifically, the processor may obtain outline information from the index map and obtain shape and position information from the saliency map, and may identify the first object  411  corresponding to the point  421  specified by the user. 
     With reference to  FIG. 4F , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may determine and display the ROI  460  of the user based on the identified first object  411 . The ROI  460  may be represented in various shapes including the identified object.  FIG. 4F  shows a ROI of the user in the form of a box, but the present invention is not limited thereto. 
       FIG. 5  is a flowchart illustrating a case where a region of interest is provided before user input. 
     Prior to operation  320  in  FIG. 3 , the processor may provide the main region of the content as a region of interest. For example, the electronic device may obtain the saliency map associated with the entire content and provide the region of interest including the main region of the entire content before receiving user input. As another example, when the region of interest has been determined based on the previous user input, the previously determined region of interest may be provided again. In such a case, operation  320  of  FIG. 3  may further include the following operations. 
     With reference to  FIG. 5 , at operation  510 , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may determine whether a preset region of interest is present. Upon determining that a preset region of interest is present, at operation  520 , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may determine whether user input is received within the preset region of interest. For example, the user may wish to identify at least one object in the preset region of interest. In some cases, the user may wish to identify an object located outside the preset region of interest. To determine the search region in consideration of the user&#39;s intention, the processor can identify the location where user input is received. 
     Upon determining that user input is received within the preset region of interest, at operation  530 , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may determine the region other than the preset region of interest as a non-search region. That is, assuming that the object that the user wishes to identify is within the preset region of interest, the processor may not search the region other than the preset region of interest for an object. 
     In various embodiments, the processor may determine a specific region included in the preset region of interest as the search region. For example, the processor may obtain a saliency map associated with the content and reflecting the main region in the preset region of interest. 
     In one embodiment, the processor may determine a portion of the preset region of interest as a search region based on at least one point specified by user input. For example, the processor may obtain an entropy map within the preset region of interest and determine a search region based on the entropy map. 
     Upon determining that user input is not received within the preset region of interest, at operation  540 , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may determine at least a portion of the content including the preset region of interest as a non-search region. That is, assuming that the object that the user wishes to identify is located outside the preset region of interest, the processor may not search the preset region of interest for an object. 
     In various embodiments, the non-search region may include a part of the region other than the preset region of interest. For example, if user input is received at some point on the right-hand side of the preset region of interest, the processor may assume that there is no object to be specified by the user on the left-hand side of the preset region of interest and determine both the preset region of interest and the left-hand side thereof as a non-search region. Alternatively, the processor may determine all regions except for the right-hand side of the preset region of interest as a non-search region. 
     When the non-search region is determined, the electronic device can determine the region other than the non-search region as a search region, and obtain a saliency map associated with the content. Alternatively, the electronic device may obtain an entropy map in a region other than the non-search region, and determine the search region based on the entropy map. 
       FIG. 6  shows an example of a ROI provided in advance. 
     The processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may output content  601  including one or more objects through the display (e.g., display device  160  in  FIG. 1 ). For example, the content  601  may include a first object  611 , a second object  612 , a third object  613 , a fourth object  614 , and a fifth object  615 . 
     In various embodiments, the processor may obtain the saliency map associated with the entire region of the content  601  and provide the ROI  620  including the main region of the entire region of the content  601  before receiving user input. Since there is no point specified by the user in the saliency map associated with the entire region of the content  601 , the processor cannot obtain a weighting matrix. In addition, since the saliency map associated with the entire region of the content  601  does not accurately reflect the outline information, a plurality of separate objects (e.g., first object  611 , second object  612 , and third object  613 ) can be identified as one object. 
       FIGS. 7A to 7C  illustrate an example of object identification when user input is received within the ROI provided in advance. 
     With reference to  FIG. 7A , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may output content  701  including one or more objects through the display (e.g., display device  160  in  FIG. 1 ). For example, the content  701  may include a first object  711 , a second object  712 , a third object  713 , a fourth object  714 , and a fifth object  715 . The processor may obtain the saliency map associated with the entire region of the content  701  and provide a preset ROI  730  including the main region of the entire region of the content  701  before receiving user input. 
     Thereafter, the processor may receive user input for specifying at least one point and may determine whether the user input is received within the preset ROI  730 . For example, to select the first object  711  contained in the preset ROI  730 , the user may touch or hover over one point  721  of the region forming the first object  711  with the pen  720  or a finger. Alternatively, the user may specify one point  721  of the region forming the first object  711  using one of non-contact recognition functions. At this time, the electronic device can determine that user input has been received within the preset ROI. 
     With reference to  FIG. 7B , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may determine the region other than the preset ROI  730  as the non-search region  741 . The processor may determine the preset ROI  730  as the search region  740 . In one embodiment, the electronic device may determine a portion of the preset ROI  730  relative to at least one point specified by user input as a search region. For example, the electronic device may obtain an entropy map associated with the content within the preset ROI  730  and determine the search region based on the entropy map. 
     With reference to  FIG. 7C , after determining the search region, the processor of the electronic device may obtain a saliency map associated with the content based on the search region, and determine a user&#39;s ROI  750  including the first object  711  based on the saliency map. In one embodiment, the processor may obtain an index map associated with the content by dividing the entire region of the content  701  into similar regions according to a preset criterion, and determine a user&#39;s ROI  750  including the first object  711  based on the saliency map and the index map. The ROI  750  may be represented in various shapes including the identified first object  711 .  FIG. 7C  shows a ROI in the form of a box, but the present invention is not limited thereto. 
       FIGS. 8A to 8C  illustrate an example of object identification when user input is received outside the ROI provided in advance. 
     With reference to  FIG. 8A , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may output content  801  including one or more objects through the display (e.g., display device  160  in  FIG. 1 ). For example, the content  801  may include a first object  811 , a second object  812 , a third object  813 , a fourth object  814 , and a fifth object  815 . The processor may obtain the saliency map associated with the entire region of the content  801  and provide a preset ROI  830  including the main region of the entire region of the content  801  before receiving user input. 
     Thereafter, the processor may receive user input for specifying at least one point and may determine whether the user input is received within the preset region of interest  830 . For example, to select the fourth object  814  located outside the preset region of interest  830 , the user may touch or hover over one point  821  of the region forming the fourth object  814  with the pen  820  or a finger. Alternatively, the user may specify one point  821  of the region forming the fourth object  814  using one of non-contact recognition functions. At this time, the electronic device can determine that user input has been received outside the preset region of interest  830 . 
     With reference to  FIG. 8B , the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may determine a region including the preset region of interest  830  as the non-search region  841 . For example, the processor may assume that the object that the user wishes to specify is outside the preset region of interest  830  and may not search the preset region of interest  830  for the object. In  FIG. 8B , the electronic device assumes that user input is received at some point on the right-hand side of the preset region of interest  830 , and determines all the region except for the right-hand side of the preset region of interest  830  as the non-search region  841 . Alternatively, the electronic device may determine the preset region of interest  830  as a non-search region, or may determine both the preset region of interest  830  and the left-hand side thereof as a non-search region. 
     When the non-search region  841  is determined, the electronic device can determine the region other than the non-search region  841  as a search region, and obtain a saliency map associated with the content  801 . Alternatively, the electronic device may obtain an entropy map in a region other than the non-search region, and determine the search region based on the entropy map. 
     With reference to  FIG. 8C , after determining the search region, the processor (e.g., processor  120  in  FIG. 1 ) of the electronic device (e.g., electronic device  101  in  FIG. 1 ) may obtain a saliency map associated with the content based on the search region  840 , and determine a user&#39;s region of interest  850  based on the saliency map. In one embodiment, the processor may obtain an index map associated with the content by dividing the entire region of the content into similar regions according to a preset criterion, and determine a user&#39;s region of interest  850  based on the saliency map and the index map. The region of interest  850  may be represented in various shapes including the identified object.  FIG. 8C  shows a ROI in the form of a box, but the present invention is not limited thereto. 
     According to various embodiments of the present invention, the method for object identification based on the region of interest may include: outputting content including one or more objects through a display (e.g., operation  310  in  FIG. 3 ); receiving user input for specifying at least one point in the entire region of the content (e.g., operation  320  in  FIG. 3 ); determining a portion of the entire region with respect to the at least one point as a search region (e.g., operation  330  in  FIG. 3 ); obtaining a saliency map associated with the content based on the search region (e.g., operation  340  in  FIG. 3 ); and determining a region of interest of the user on the basis of the saliency map (e.g., operation  360  in  FIG. 3 ). 
     In one embodiment, the object identification method based on the region of interest may further include obtaining an index map associated with the content by dividing the entire region of the content into similar regions according to a preset criterion (e.g., operation  350  in  FIG. 3 ). The region of interest of the user may be determined on the basis of the saliency map and the index map (e.g., operation  370  in  FIG. 3 ). 
     In one embodiment, the object identification method based on the region of interest may further include examining relative variations between one or more pixels constituting the content or blocks including multiple pixels and obtaining an entropy map related to the content based on the relative variations. 
     In one embodiment, the object identification method based on the region of interest may further include: dividing the entropy map according to a specific criterion; identifying at least one region to which the point specified by the user belongs; calculating the statistical characteristics of the identified region; finding additional regions having statistical characteristics similar to those of the identified region; and determining the search region as including the identified region and the found additional regions. 
     In one embodiment, the object identification method based on the region of interest may further include: generating a weighting matrix based on the point specified by the user; and obtaining a weighted saliency map by applying the weighting matrix to at least a portion of the saliency map. 
     In one embodiment, the preset criterion may be at least one of color, outline, and contrast. 
     In one embodiment, the object identification method based on the region of interest may further include identifying an object according to the point specified by the user by overlapping main regions in the saliency map and similar regions in the index map. 
     In one embodiment, the object identification method based on the region of interest may further include: providing a main region of the content as a preset region of interest (e.g., operation  510  in  FIG. 5 ); and determining, if a user input is received within the preset region of interest, a region other than the preset region of interest as a non-search region (e.g., operation  530  in  FIG. 5 ). 
     In one embodiment, the object identification method based on the region of interest may further include: providing a main region of the content as a preset region of interest (e.g., operation  510  in  FIG. 5 ); and determining, if a user input is not received within the preset region of interest, at least a portion of the content including the preset region of interest as a non-search region (e.g., operation  540  in  FIG. 5 ). 
     In one embodiment, the user input for the object identification method may be received by utilizing at least one of touch input using a portion of the human body or a pen, hovering input using a portion of the human body or a pen, and non-contact recognition. 
     The electronic device according to various embodiments may be one of various types of electronic devices. The electronic devices may include, for example, a portable communication device (e.g., a smart phone), a computer device, a portable multimedia device, a portable medical device, a camera, a wearable device, or a home appliance. According to an embodiment of the disclosure, the electronic devices are not limited to those described above. 
     It should be appreciated that various embodiments of the present disclosure and the terms used therein are not intended to limit the technological features set forth herein to particular embodiments and include various changes, equivalents, or replacements for a corresponding embodiment. With regard to the description of the drawings, similar reference numerals may be used to refer to similar or related elements. It is to be understood that a singular form of a noun corresponding to an item may include one or more of the things, unless the relevant context clearly indicates otherwise. As used herein, each of such phrases as “A or B,” “at least one of A and B,” “at least one of A or B,” “A, B, or C,” “at least one of A, B, and C,” and “at least one of A, B, or C,” may include all possible combinations of the items enumerated together in a corresponding one of the phrases. As used herein, such terms as “1st” and “2nd,” or “first” and “second” may be used to simply distinguish a corresponding component from another, and does not limit the components in other aspect (e.g., importance or order). It is to be understood that if an element (e.g., a first element) is referred to, with or without the term “operatively” or “communicatively”, as “coupled with,” “coupled to,” “connected with,” or “connected to” another element (e.g., a second element), it means that the element may be coupled with the other element directly (e.g., wiredly), wirelessly, or via a third element. 
     As used herein, the term “module” may include a unit implemented in hardware, software, or firmware, and may interchangeably be used with other terms, for example, “logic,” “logic block,” “part,” or “circuitry”. A module may be a single integral component, or a minimum unit or part thereof, adapted to perform one or more functions. For example, according to an embodiment, the module may be implemented in a form of an application-specific integrated circuit (ASIC). 
     Various embodiments as set forth herein may be implemented as software (e.g., the program  140 ) including one or more instructions that are stored in a storage medium (e.g., internal memory  136  or external memory  138 ) that is readable by a machine (e.g., the electronic device  101 ). For example, a processor (e.g., the processor  120 ) of the machine (e.g., the electronic device  101 ) may invoke at least one of the one or more instructions stored in the storage medium, and execute it, with or without using one or more other components under the control of the processor. This allows the machine to be operated to perform at least one function according to the at least one instruction invoked. The one or more instructions may include a code generated by a complier or a code executable by an interpreter. The machine-readable storage medium may be provided in the form of a non-transitory storage medium. Wherein, the term “non-transitory” simply means that the storage medium is a tangible device, and does not include a signal (e.g., an electromagnetic wave), but this term does not differentiate between where data is semi-permanently stored in the storage medium and where the data is temporarily stored in the storage medium. 
     According to an embodiment, a method according to various embodiments of the disclosure may be included and provided in a computer program product. The computer program product may be traded as a product between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., compact disc read only memory (CD-ROM)), or be distributed (e.g., downloaded or uploaded) online via an application store (e.g., Play Store™), or between two user devices (e.g., smart phones) directly. If distributed online, at least part of the computer program product may be temporarily generated or at least temporarily stored in the machine-readable storage medium, such as memory of the manufacturer&#39;s server, a server of the application store, or a relay server. 
     According to various embodiments, each component (e.g., a module or a program) of the above-described components may include a single entity or multiple entities. According to various embodiments, one or more of the above-described components may be omitted, or one or more other components may be added. Alternatively or additionally, a plurality of components (e.g., modules or programs) may be integrated into a single component. In such a case, according to various embodiments, the integrated component may still perform one or more functions of each of the plurality of components in the same or similar manner as they are performed by a corresponding one of the plurality of components before the integration. According to various embodiments, operations performed by the module, the program, or another component may be carried out sequentially, in parallel, repeatedly, or heuristically, or one or more of the operations may be executed in a different order or omitted, or one or more other operations may be added. 
     Although the present disclosure has been described with various embodiments, various changes and modifications may be suggested to one skilled in the art. It is intended that the present disclosure encompass such changes and modifications as fall within the scope of the appended claims.