Shree Nayar
Columbia University in the City of New York
H-index: 134
North America-United States
Description
Shree Nayar, With an exceptional h-index of 134 and a recent h-index of 61 (since 2020), a distinguished researcher at Columbia University in the City of New York, specializes in the field of Computer Vision, Computational Imaging, Computational Photography, Computer Graphics, Robotics.
His recent articles reflect a diverse array of research interests and contributions to the field:
Management of pseudorandom animation system
Fast data accessing system using optical beacons
Personalized emoji dictionary
Client device processing received emoji-first messages
Low power light wave communication for mobile and wearable devices
Long distance QR code decoding
Trackpad on back portion of a device
Emoji-first messaging
Professor Information
University | Columbia University in the City of New York |
---|---|
Position | Professor of Computer Science |
Citations(all) | 68170 |
Citations(since 2020) | 16710 |
Cited By | 58416 |
hIndex(all) | 134 |
hIndex(since 2020) | 61 |
i10Index(all) | 274 |
i10Index(since 2020) | 180 |
University Profile Page | Columbia University in the City of New York |
Research & Interests List
Computer Vision
Computational Imaging
Computational Photography
Computer Graphics
Robotics
Top articles of Shree Nayar
Management of pseudorandom animation system
Methods, devices, media, and other embodiments are described for managing and configuring a pseudorandom animation system and associated computer animation models. One embodiment involves generating image modification data with a computer animation model configured to modify frames of a video image to insert and animate the computer animation model within the frames of the video image, where the computer animation model of the image modification data comprises one or more control points. Motion patterns and speed harmonics are automatically associated with the control points, and motion states are generated based on the associated motions and harmonics. A probability value is then assigned to each motion state. The motion state probabilities can then be used when generating a pseudorandom animation.
Published Date
2024/1/11
Fast data accessing system using optical beacons
An apparatus to perform fast data access comprises a receiver, a processor, and a memory. The processor receives using the receiver a light signal from a light source. The light signal can be structured to generate a temporal code. The light source is an optical beacon that includes a Light-Emitting Diode (LED). The processor then decodes the light signal to generate a network address, and causes a display of a client device coupled to the apparatus to display information based on the network address. The network address can be a Uniform Resource Locator (URL) address and the information based on the network address includes a webpage associated with the URL. Other embodiments are described herein.
Published Date
2023/11/21
Personalized emoji dictionary
A personalized emoji dictionary, such as for use with emoji-first messaging. Text messaging is automatically converted to emojis by an emoji-first application so that only emojis are communicated from one client device to another client device. Each client device has a personalized emoji library of emojis that are mapped to words, which libraries are customizable and unique to the users of the client devices, such that the users can communicate secretly in code. Upon receipt of a string of emojis, a user can select the emoji string to convert to text if desired, for a predetermined period of time.
Published Date
2024/1/2
Client device processing received emoji-first messages
A client device processing received emoji messages using emoji-first messaging. Text messaging is automatically converted to emojis by an emoji-first application so that only emojis are communicated from one client device to another client device. Each client device has a library of emojis that are mapped to words, which libraries are customizable and unique to the users of the client devices, such that the users can communicate secretly in code. Upon receipt of a string of emojis, a user can select the emoji string to convert to text if desired, for a predetermined period of time.
Published Date
2024/2/20
Low power light wave communication for mobile and wearable devices
A client device, such as a mobile phone or a mobile phone accessory (eg, phone case), is provided that receives and transmits data (eg, a social media code) via light wave communication. The light wave communication may comprise structured light (eg, projected light patterns). The client device may include a lightbox comprised of LEDs located on a back face of the client device.
Published Date
2024/2/13
Long distance QR code decoding
Systems and methods are provided for: receiving an image containing a code that has one or more visual qualities that fail to satisfy respective thresholds; applying a trained machine learning model to find a rough location of the code by generating a bounding box and cropping out the portion of the image; applying another trained machine learning model to the portion of the image to estimate key point locations of the code depicted in the portion of the image, aligning the portion of the image that depicts the code based on the estimated key point locations; and decoding, by the other trained machine learning model, the aligned portion of the image that depicts the code.
Published Date
2024/4/9
Trackpad on back portion of a device
Aspects of the present disclosure involve a system and a method for performing operations comprising: detecting physical touch of a touch-sensitive component on a back portion of a client device, the client device displaying a graphical user interface on a touch-sensitive display screen of a front portion of the client device; in response to detecting the physical touch, transmitting an electrical signal representing the physical touch of the touch-sensitive component on the back portion of the client device to the touch-sensitive display screen of the front portion of the client device; and causing an operation associated with the graphical user interface to be executed in response to the touch-sensitive display screen receiving the electrical signal representing the physical touch of the touch-sensitive component on the back portion of the client device.
Published Date
2024/1/30
Emoji-first messaging
Emoji-first messaging where text messaging is automatically converted to emojis by an emoji-first application so that only emojis are communicated from one client device to another client device. Each client device has a library of emojis that are mapped to words, which libraries are customizable and unique to the users of the client devices, such that the users can communicate secretly in code. Upon receipt of a string of emojis, a user can select the emoji string to convert to text if desired, for a predetermined period of time.
Published Date
2024/1/30
Professor FAQs
What is Shree Nayar's h-index at Columbia University in the City of New York?
The h-index of Shree Nayar has been 61 since 2020 and 134 in total.
What are Shree Nayar's top articles?
The articles with the titles of
Management of pseudorandom animation system
Fast data accessing system using optical beacons
Personalized emoji dictionary
Client device processing received emoji-first messages
Low power light wave communication for mobile and wearable devices
Long distance QR code decoding
Trackpad on back portion of a device
Emoji-first messaging
...
are the top articles of Shree Nayar at Columbia University in the City of New York.
What are Shree Nayar's research interests?
The research interests of Shree Nayar are: Computer Vision, Computational Imaging, Computational Photography, Computer Graphics, Robotics
What is Shree Nayar's total number of citations?
Shree Nayar has 68,170 citations in total.
What are the co-authors of Shree Nayar?
The co-authors of Shree Nayar are Takeo Kanade, Ramesh Raskar, Ravi Ramamoorthi, Terrance E. Boult, Peter Belhumeur, Srinivasa Narasimhan.