Abstract: Disclosed herein are methods and systems for providing multivariate time series clustering for customer segmentation. The system comprises of a model management unit that devices a customer segmentation procedure based on temporal variations of user preferences, using MTS clustering, and utilize the discovered clusters to learn association rules specific to each clusters, and improves campaign targeting. The order of the VAR model is fixed based on the nature of the data and length of the time series.

Abstract: A method and system for continuously authenticating a user working from a remote location is provided. The method includes providing user an interface to login through his login credentials to company domain. The login credentials are authenticated by a company's remote server. Once the user is authenticated the server pushes user's secondary authentication details to user's device and invokes a secondary authentication system. The secondary authentication system may include a webcam that initiates once user is logged in and continuously monitors biometric parameters for continued authentication of the user.

Abstract: A method of providing content is provided. The method includes: receiving, by a target device, first content from a source device; establishing, by the target device, a connection with a cloud computing device; transmitting, by the target device, the first content and content control information to be used to convert the first content, to the cloud computing device; and receiving, by the target device, second content obtained by converting the first content based on the content control information, from the cloud computing device.

Abstract: An image sensor device may include an array of image sensing pixels with adjacent image sensing pixels being arranged in macropixel, and a processor coupled to the array of image sensing pixels. The processor may be configured to receive pixel signals from the array of image sensing pixels, and arrange the received pixel signals into macropixel signal sets for respective macropixels. The processor may be configured to perform, in parallel, an image enhancement operation on the received pixel signals for each macropixel signal set to generate enhanced macropixel signals, and transmit the enhanced macropixel signals.

Abstract: A method and system for continuously authenticating a user working from a remote location is provided. The method includes providing user an interface to login through his login credentials to company domain. The login credentials are authenticated by a company's remote server. Once the user is authenticated the server pushes user's secondary authentication details to user's device and invokes a secondary authentication system. The secondary authentication system may include a webcam that initiates once user is logged in and continuously monitors biometric parameters for continued authentication of the user.

Abstract: An image sensor device may include an array of image sensing pixels with adjacent image sensing pixels being arranged in macropixel, and a processor coupled to the array of image sensing pixels. The processor may be configured to receive pixel signals from the array of image sensing pixels, and arrange the received pixel signals into macropixel signal sets for respective macropixels. The processor may be configured to perform, in parallel, an image enhancement operation on the received pixel signals for each macropixel signal set to generate enhanced macropixel signals, and transmit the enhanced macropixel signals.

Abstract: An image sensor device may include an array of image sensing pixels with adjacent image sensing pixels being arranged in macropixel, and a processor coupled to the array of image sensing pixels. The processor may be configured to receive pixel signals from the array of image sensing pixels, and arrange the received pixel signals into macropixel signal sets for respective macropixels. The processor may be configured to perform, in parallel, an image enhancement operation on the received pixel signals for each macropixel signal set to generate enhanced macropixel signals, and transmit the enhanced macropixel signals.

Abstract: An image sensor device may include an array of image sensing pixels with adjacent image sensing pixels being arranged in macropixel, and a processor coupled to the array of image sensing pixels. The processor may be configured to receive pixel signals from the array of image sensing pixels, and arrange the received pixel signals into macropixel signal sets for respective macropixels. The processor may be configured to perform, in parallel, an image enhancement operation on the received pixel signals for each macropixel signal set to generate enhanced macropixel signals, and transmit the enhanced macropixel signals.

Abstract: An image sensor device may include an array of image sensing pixels with adjacent image sensing pixels being arranged in macropixel, and a processor coupled to the array of image sensing pixels. The processor may be configured to receive pixel signals from the array of image sensing pixels, and arrange the received pixel signals into macropixel signal sets for respective macropixels. The processor may be configured to perform, in parallel, an image enhancement operation on the received pixel signals for each macropixel signal set to generate enhanced macropixel signals, and transmit the enhanced macropixel signals.

Abstract: A video compression framework based on parametric object and background compression is proposed. At the encoder, an embodiment detects objects and segments frames into regions corresponding to the foreground object and the background. The object and the background are individually encoded using separate parametric coding techniques. While the object is encoded using the projection of coefficients to the orthonormal basis of the learnt subspace (used for appearance based object tracking), the background is characterized using an auto-regressive (AR) process model. An advantage of the proposed schemes is that the decoder structure allows for simultaneous reconstruction of object and background, thus making it amenable to the new multi-thread/multi-processor architectures.

Abstract: Disclosed herein are methods and systems for providing multivariate time series clustering for customer segmentation. The system comprises of a model management unit that devices a customer segmentation procedure based on temporal variations of user preferences, using MTS clustering, and utilize the discovered clusters to learn association rules specific to each clusters, and improves campaign targeting. The order of the VAR model is fixed based on the nature of the data and length of the time series.

Abstract: An image sensor device may include an array of image sensing pixels with adjacent image sensing pixels being arranged in macropixel, and a processor coupled to the array of image sensing pixels. The processor may be configured to receive pixel signals from the array of image sensing pixels, and arrange the received pixel signals into macropixel signal sets for respective macropixels. The processor may be configured to perform, in parallel, an image enhancement operation on the received pixel signals for each macropixel signal set to generate enhanced macropixel signals, and transmit the enhanced macropixel signals.

Abstract: System and method for identifying erroneous videos and assessing video quality is provided. Feature vectors are generated corresponding to a plurality of frames associated with the one or more videos. The feature vectors are subsequently subjected to anomaly detection to obtain first and second normalized path lengths and normalized anomaly measures. The first and second normalized path lengths and normalized anomaly measures are provided to a regression model to identify the erroneous video.

Abstract: A method of providing content is provided. The method includes: receiving, by a target device, first content from a source device; establishing, by the target device, a connection with a cloud computing device; transmitting, by the target device, the first content and content control information to be used to convert the first content, to the cloud computing device; and receiving, by the target device, second content obtained by converting the first content based on the content control information, from the cloud computing device.

Abstract: System and method for identifying erroneous videos and assessing video quality is provided. Feature vectors are generated corresponding to a plurality of frames associated with the one or more videos. The feature vectors are subsequently subjected to anomaly detection to obtain first and second normalized path lengths and normalized anomaly measures. The first and second normalized path lengths and normalized anomaly measures are provided to a regression model to identify the erroneous video.

Abstract: A video compression framework based on parametric object and background compression is proposed. At the encoder, an embodiment detects objects and segments frames into regions corresponding to the foreground object and the background. The object and the background are individually encoded using separate parametric coding techniques. While the object is encoded using the projection of coefficients to the orthonormal basis of the learnt subspace (used for appearance based object tracking), the background is characterized using an auto-regressive (AR) process model. An advantage of the proposed schemes is that the decoder structure allows for simultaneous reconstruction of object and background, thus making it amenable to the new multi-thread/multi-processor architectures.

Abstract: A video compression framework based on parametric object and background compression is proposed. At the encoder, an embodiment detects objects and segments frames into regions corresponding to the foreground object and the background. The object and the background are individually encoded using separate parametric coding techniques. While the object is encoded using the projection coefficients to the orthonormal basis of the learnt subspace (used for appearance based object tracking), the background is characterized using an auto-regressive (AR) process model. An advantage of the proposed schemes is that the decoder structure allows for simultaneous reconstruction of object and background, thus making it amenable to the new multi-thread/multi-processor architectures.

Abstract: A video compression framework based on parametric object and background compression is proposed. At the encoder, an embodiment detects objects and segments frames into regions corresponding to the foreground object and the background. The object and the background are individually encoded using separate parametric coding techniques. While the object is encoded using the projection of coefficients to the orthonormal basis of the learnt subspace (used for appearance based object tracking), the background is characterized using an auto-regressive (AR) process model. An advantage of the proposed schemes is that the decoder structure allows for simultaneous reconstruction of object and background, thus making it amenable to the new multi-thread/multi-processor architectures.