Abstract:
An object tracking method includes generating a feature map of a search image and generating a feature map of a target image, obtaining an object classification result and a basic bounding box based on the feature map of the search image and the feature map of the target image, obtaining an auxiliary bounding box based on the feature map of the search image, obtaining a final bounding box based on the basic bounding box and the auxiliary bounding box, and tracking an object based on the object classification result and the final bounding box.
Abstract:
A processor-implemented neural network data processing method includes: determining a total number of either one of a first feature value and values less than or equal to the first feature value, in feature data output from a layer of a neural network; determining a quantization parameter based on the determined number; quantizing the feature data based on the determined quantization parameter; and inputting the quantized feature data to a another layer of the neural network connected to the layer.
Abstract:
Disclosed is a face verification method and apparatus. The method including analyzing a current frame of a verification image, determining a current frame state score of the verification image indicating whether the current frame is in a state predetermined as being appropriate for verification, determining whether the current frame state score satisfies a predetermined validity condition, and selectively, based on a result of the determining of whether the current frame state score satisfies the predetermined validity condition, extracting a feature from the current frame and performing verification by comparing a determined similarity between the extracted feature and a registered feature to a set verification threshold.
Abstract:
A lightened neural network, method, and apparatus, and recognition method and apparatus implementing the same. A neural network includes a plurality of layers each comprising neurons and plural synapses connecting neurons included in neighboring layers. Synaptic weights with values greater than zero and less than a preset value of a variable a, which is greater than zero, may be at least partially set to zero. Synaptic weights with values greater than a preset value of a variable b, which is greater than zero, may be at least partially set to the preset value of the variable b.
Abstract:
An image matching method includes extracting, from a first image of an object, a landmark patch including a landmark point of the object; extracting, from a second image of the object, a target patch corresponding to the landmark patch; and determining a target point in the second image corresponding to the landmark point based on a matching between the landmark patch and the target patch.
Abstract:
Disclosed is a face verification method and apparatus. The method including analyzing a current frame of a verification image, determining a current frame state score of the verification image indicating whether the current frame is in a state predetermined as being appropriate for verification, determining whether the current frame state score satisfies a predetermined validity condition, and selectively, based on a result of the determining of whether the current frame state score satisfies the predetermined validity condition, extracting a feature from the current frame and performing verification by comparing a determined similarity between the extracted feature and a registered feature to a set verification threshold.
Abstract:
A lightened neural network, method, and apparatus, and recognition method and apparatus implementing the same. A neural network includes a plurality of layers each comprising neurons and plural synapses connecting neurons included in neighboring layers. Synaptic weights with values greater than zero and less than a preset value of a variable a, which is greater than zero, may be at least partially set to zero. Synaptic weights with values greater than a preset value of a variable b, which is greater than zero, may be at least partially set to the preset value of the variable b.
Abstract:
Adaptive time/frequency-based audio encoding and decoding apparatuses and methods. The encoding apparatus includes a transformation & mode determination unit to divide an input audio signal into a plurality of frequency-domain signals and to select a time-based encoding mode or a frequency-based encoding mode for each respective frequency-domain signal, an encoding unit to encode each frequency-domain signal in the respective encoding mode, and a bitstream output unit to output encoded data, division information, and encoding mode information for each respective frequency-domain signal. In the apparatuses and methods, acoustic characteristics and a voicing model are simultaneously applied to a frame, which is an audio compression processing unit. As a result, a compression method effective for both music and voice can be produced, and the compression method can be used for mobile terminals that require audio compression at a low bit rate.
Abstract:
An image sensor includes: a motion detection circuit configured to detect a motion in image frames; and a micro control unit (MCU) configured to adjust at least a portion of a target frame among the image frames based on whether the motion is detected, and detect whether a target object is present based on the adjusted portion of the target frame.
Abstract:
Disclosed is a face verification method and apparatus. The method including analyzing a current frame of a verification image, determining a current frame state score of the verification image indicating whether the current frame is in a state predetermined as being appropriate for verification, determining whether the current frame state score satisfies a predetermined validity condition, and selectively, based on a result of the determining of whether the current frame state score satisfies the predetermined validity condition, extracting a feature from the current frame and performing verification by comparing a determined similarity between the extracted feature and a registered feature to a set verification threshold.