The thermal camera can capture keyboard surface temperature change after a human's touch. This phenomenon may be used to steal users' passwords physically. In this paper, based on the study of thermal dynamics of keyboards, we design a password break system using an infrared thermal camera. First, we build a signal model to describe the dynamic process of temperature change on the keyboard using Newton's law of cooling. Next, we develop a maximum likelihood parameter estimation algorithm to estimate the keystroke time instants. Then, by maximizing the probability of key order arrangement, a novel password breaking algorithm is developed. Our algorithm is tested using simulated data as well as real-world data. Experiment results show that our algorithm is effective for physical password breaking using thermal characteristics. Based on our results, we discuss strategies for password protection at the end.
Additive manufacturing (AM, or 3D printing) is a novel manufacturing technology that has been adopted in industrial and consumer settings. However, the reliance of this technology on computerization has raised various security concerns. In this paper, we address issues associated with sabotage via tampering during the 3D printing process by presenting an approach that can verify the integrity of a 3D printed object. Our approach operates on acoustic side-channel emanations generated by the 3D printer's stepper motors, which results in a non-intrusive and real-time validation process that is difficult to compromise. The proposed approach constitutes two algorithms. The first algorithm is used to generate a master audio fingerprint for the verifiable unaltered printing process. The second algorithm is applied when the same 3D object is printed again, and this algorithm validates the monitored 3D printing process by assessing the similarity of its audio signature with the master audio fingerprint. To evaluate the quality of the proposed thresholds, we identify the detectability thresholds for the following minimal tampering primitives: insertion, deletion, replacement, and modification of a single tool path command. By detecting the deviation at the time of occurrence, we can stop the printing process for compromised objects, thus saving time and preventing material waste. We discuss various factors that impact the method, such as background noise, audio device changes, and different audio recorder positions.
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For our January 2019 issue, we cover recent patents granted in the area of face recognition.
In one embodiment no. 10,162,999, a method includes accessing an image file associated with a first user of a communication system and detecting a face in an image corresponding to the image file. The method also includes accessing an event database associated with the communication system, the event database containing one or more events, each being associated with the first user and one or more second users of the communication system. The method also includes determining one or more candidates among the second users to be matched to the face, where each candidate is associated with an event in the communication system, and where a time associated with the image is in temporal proximity to a time associated with the event
Patent no. 10,146,797 presents methods, systems, and apparatus, including computer programs encoded on computer storage media, for storing facial recognition image data in a cache. One of the methods includes receiving an image from a camera, detecting, in the received image, a face of a person, searching a biometric data cache based on the detected face, in response to searching the biometric data cache based on the detected face, determining whether the biometric data cache includes data for the person, in response to a determination that the biometric data cache includes data for the person, using the data from the biometric data cache to determine an identifier for the person, and in response to a determination that the biometric data cache does not include data for the person: searching a data storage system based on the detected face of the person to determine whether the data storage system includes data for the person.
According to patent no. 10,108,851 a video conference invite is accessed and names and/or account addresses in the invite are used to obtain information of people listed on the invite from a database. The information can include template photographs of the people and locations of the people. During a video conference that is subject of the invite, when it is determined that a video feed of the video conference indicates that plural participants are together in a single room, images of faces in the video feed are efficiently matched against only template photographs of people in the database indicated by the database as being associated with the room.
Patent no. 10,102,421 presents a method for face recognition in the video comprises: performing feature extraction on a target face in multiple image frames in the video to generate multiple face feature vectors respectively corresponding to the target face in the multiple image frames; performing time sequence feature extraction on the plurality of face feature vectors to convert the plurality of face feature vectors into a feature vector of a predetermined dimension; and judging the feature vector of the predetermined dimension by using a classifier so as to recognize the target face.
The invention no. 10,061,996 comprises capturing an image of a subject to be authenticated; a step of face verification; followed by the process steps of a scan line detection test, a specular reflection detection test, and a chromatic moment and color diversity feature analysis test in no particular order. The method requires a subject to present her face before a camera, which can be the built-in or peripheral camera of e.g. a mobile communication device or a mobile computing device. The method also requires displaying to the subject certain instructions and the real-time video feedback of the subject face on a display screen, which can be the built-in or peripheral display screen of the mobile communication device or mobile computing device.
In patent no. 10,033,973 systems and methods for customizing a personalized user interface of an IP video door phone using face recognition are provided. Methods can include receiving an image of a user captured by a camera, performing face recognition processing on the image to identify an age of the user, identifying a customized user interface associated with the age of the user, and causing a display screen to display the customized user interface.
A system presented in patent no. 10,026,022 trains a facial recognition modeling system using an extremely large data set of facial images, by distributing a plurality of facial recognition models across a plurality of nodes within the facial recognition modeling system. The system optimizes a facial matching accuracy of the facial recognition modeling system by increasing a facial image set variance among the plurality of facial recognition models. The system selectively matches each facial image within the extremely large data set of facial images with at least one of the plurality of facial recognition models. The system reduces the time associated with training the facial recognition modeling system by load balancing the extremely large data set of facial images across the plurality of facial recognition models while improving the facial matching accuracy associated with each of the plurality of facial recognition models.
The disclosure no. 10,019,624 relates to a face recognition system. The face recognition system includes a camera module configured to acquire face recognition information of a target object; a feature point recognition module configured to select facial feature points; a displacement output module configured to output a displacement and azimuth of the camera module during acquiring the face recognition information at different positions; a distance calculation module configured to calculate depth distances between the facial feature points and the displacement between the different positions; and a face recognition module configured to judge whether the target object is the target user. A face recognition method is also related.
If you have an interesting patent to share when we next feature patents related to face recognition, or if you are especially interested in a signal processing research field that you would want to be highlighted in this section, please send email to Csaba Benedek (benedek.csaba AT sztaki DOT mta DOT hu).
Title: Face recognition based on spatial and temporal proximity
Inventors: Papakipos; Phaedra (Palo Alto, CA), Papakipos; Matthew Nicholas (Portola Valley, CA)
Issued: December 25, 2018
Assignee: Facebook, Inc. (Menlo Park, CA)
Title: Face recognition image data cache
Inventors: Bataller; Cyrille (Mougins, FR), Astrom; Anders (Villa Marina, SG), Schiopu; Vitalie (Luxembourg, LU), Khalafi; Hakim (Amsterdam, NL)
Issued: December 4, 2018
Assignee: Accenture Global Services Limited (Dublin, IE)
Title: Face recognition in an enterprise video conference
Inventors: Bandameedipalli; Jyothsna (Karnataka, IN), Agrawal; Amit Kumar (Karnataka, IN)
Issued: October 23, 2018
Assignee: Motorola Mobility LLC (Chicago, IL)
Title: Method and device for face recognition in video
Inventors: Zhou; Erjin (Beijing, CN), Yin; Qi (Beijing, CN)
Issued: October 16, 2018
Assignee: Pinhole (Beijing) Technology Co., LTD. (Beijing, CN)
Title: Face recognition method and system for personal identification and authentication
Inventors: Chow; Felix (Hong Kong, HK), Ng; Chiu Wa (Hong Kong, HK), Yip; Chun Ho (Hong Kong, HK), Lau; How Chun (Hong Kong, HK)
Issued: August 28, 2018
Assignee: Hampen Technology Corporation Limited (Hong Kong, HK)
Title: Systems and methods for customizing a personalized user interface using face recognition
Inventors: Shen; Jiehong (Shanghai, CN), Yang; Xiukuan (Shanghai, CN), Li; Peng (Shanghai, CN)<
Issued: July 24, 2018
Assignee: Honeywell International Inc. (Morristown, NJ)
Title: Face recognition in big data ecosystem using multiple recognition models
Inventors: Asati; Somnath (Chhatarpur, IN), Naganna; Soma Shekar (Bangalore, IN), Seth; Abhishek (Uttar Pradesh, IN), Tomar; Vishal (Meerut, IN), Yellareddy; Shashidhar R. (Bangalore, IN)
Issued: July 17, 2018
Assignee: International Business Machines Corporation (Armonk, NY)
Title: Face recognition system and face recognition method
Inventors: Liu; Tien-Ping (New Taipei, TW), Hung; Yu-Tai (New Taipei, TW), Yang; Fu-Hsiung (New Taipei, TW)<
Issued: July 10, 2018
Assignee: Hon Hai Precision Industry Co., LTD. (New Taipei, TW)
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