1860 results about "Frame sequence" patented technology

A multi-dimensional database and indexes and operations on the multi-dimensional database are described which include video search applications or other similar sequence or structure searches. Traversal indexes utilize highly discriminative information about images and video sequences or about object shapes. Global and local signatures around keypoints are used for compact and robust retrieval and discriminative information content of images or video sequences of interest. For other objects or structures relevant signature of pattern or structure are used for traversal indexes. Traversal indexes are stored in leaf nodes along with distance measures and occurrence of similar images in the database. During a sequence query, correlation scores are calculated for single frame, for frame sequence, and video clips, or for other objects or structures.

A method for generating an index of the text of a video image sequence is provided. The method includes the steps of determining the image text objects in each of a plurality of frames of the video image sequence; comparing the image text objects in each of the plurality of frames of the video image sequence to obtain a record of frame sequences having matching image text objects; extracting the content for each of the similar image text objects in text string format; and storing the text string for each image text object as a video text object in a retrievable medium.

A method and system generates and compares fingerprints for videos in a video library. The video fingerprints provide a compact representation of the temporal locations of discontinuities in the video that can be used to quickly and efficiently identify video content. Discontinuities can be, for example, shot boundaries in the video frame sequence or silent points in the audio stream. Because the fingerprints are based on structural discontinuity characteristics rather than exact bit sequences, visual content of videos can be effectively compared even when there are small differences between the videos in compression factors, source resolutions, start and stop times, frame rates, and so on. Comparison of video fingerprints can be used, for example, to search for and remove copyright protected videos from a video library. Furthermore, duplicate videos can be detected and discarded in order to preserve storage space.

A long-term memory used to store and retrieve information learned while a video analysis system observes a stream of video frames is disclosed. The long-term memory provides a memory with a capacity that grows in size gracefully, as events are observed over time. Additionally, the long-term memory may encode events, represented by sub-graphs of a neural network. Further, rather than predefining a number of patterns recognized and manipulated by the long-term memory, embodiments of the invention provide a long-term memory where the size of a feature dimension (used to determine the similarity between different observed events) may grow dynamically as necessary, depending on the actual events observed in a sequence of video frames.

The invention discloses a video behavior identification method based on spatio-temporal fusion characteristics and attention mechanism, The spatio-temporal fusion feature of input video is extracted by convolution neural network Inception V3, and then combining with the attention mechanism of human visual system on the basis of spatio-temporal fusion characteristics, the network can automaticallyallocate weights according to the video content, extract the key frames in the video frame sequence, and identify the behavior from the video as a whole. Thus, the interference of redundant information on the identification is eliminated, and the accuracy of the video behavior identification is improved.

An apparatus and method for the analysis of a sequence of captured images covering a scene for detecting and tracking of moving and static objects (86) and for matching (88) the patterns of object behavior in the captured images to object behavior in predetermined scenarios.

A technique for digital video processing in a predictive manner is provided. In one embodiment, a method for processing digital video signals for live video applications comprises providing video data that comprise a plurality of frames, identifying a first frame and a second frame in the frame sequences, and processing the information of the first frame and the information of the second frame to determine a quantization step for the second frame. The step of processing the information of the first frame and the information of the second frame further comprises calculating a sigmaSAD value for the second frame, calculating a divisor value for the second frame, and calculating the quantization step for the second frame. In another embodiment, a system for processing digital video signals for live video applications comprises a memory unit within which a computer program is stored. The computer program instructs the system to process digital video in a predicative manner. In yet another embodiment, a system for processing digital video signals for live video applications comprises various subsystems that together process digital video in a predictive manner.

Techniques are disclosed for a computer vision engine to update both a background model and thresholds used to classify pixels as depicting scene foreground or background in response to detecting that a sudden illumination changes has occurred in a sequence of video frames. The threshold values may be used to specify how much pixel a given pixel may differ from corresponding values in the background model before being classified as depicting foreground. When a sudden illumination change is detected, the values for pixels affected by sudden illumination change may be used to update the value in the background image to reflect the value for that pixel following the sudden illumination change as well as update the threshold for classifying that pixel as depicting foreground/background in subsequent frames of video.

A video stabilization method includes: measuring an inter-frame camera motion based on a difference angle of a relative camera view direction in comparison with a reference camera view direction in each frame of a frame sequence of a video; generating a camera motion path of the frame sequence by using the inter-frame camera motion and determining a camera view direction adjustment angle based on a user's view direction by using the camera motion path; and compensating for the camera view direction by using the camera view direction adjustment angle in each frame.

The invention discloses a video description method based on deep learning and text summarization. The video description method comprises the following steps: through a traditional image data set, training a convolutional neural network model according to an image classification task; extracting a video frame sequence of a video, utilizing the convolutional neural network model to extract convolutional neural network characteristics to form a <video frame sequence, text description sequence> pair which is used as the input of a recurrent neural network model, and training to obtain the recurrent neural network model; describing the video frame sequence of the video to be described through the recurrent neural network model obtained by training to obtain description sequences; and through a method that graph-based vocabulary centrality is used as the significance of the text summarization, sorting the description sequences, and outputting a final description result of the video. An event which happens in one video and object attributes associated with the event are described through a natural language so as to achieve a purpose that video contents are described and summarized.

The invention discloses a bidirectional long short-term memory unit-based behavior identification method for a video. The method comprises the steps of (1) inputting a video sequence and extracting an RGB (Red, Green and Blue) frame sequence and an optical flow image from the video sequence; (2) respectively training a deep convolutional network of an RGB image and a deep convolutional network of the optical flow image; (3) extracting multilayer characteristics of the network, wherein characteristics of a third convolutional layer, a fifth convolutional layer and a seventh fully connected layer are at least extracted, and the characteristics of the convolutional layers are pooled; (4) training a recurrent neural network constructed by use of a bidirectional long short-term memory unit to obtain a probability matrix of each frame of the video; and (5) averaging the probability matrixes, finally fusing the probability matrixes of an optical flow frame and an RGB frame, taking a category with a maximum probability as a final classification result, and thus realizing behavior identification. According to the method, the conventional artificial characteristics are replaced with multi-layer depth learning characteristics, the depth characteristics of different layers represent different pieces of information, and the combination of multi-layer characteristics can improve the accuracy rate of classification; and the time information is captured by use of the bidirectional long short-term memory, many pieces of time domain structural information are obtained and a behavior identification effect is improved.

The invention relates to voice detection technology in an automatic caption generating system, in particular to a self-adaptive voice endpoint detection method. The method comprises the following steps: dividing an audio sampling sequence into frames with fixed lengths, and forming a frame sequence; extracting three audio characteristic parameters comprising short-time energy, short-time zero-crossing rate and short-time information entropy aiming at data of each frame; calculating short-time energy frequency values of the data of each frame according to the audio characteristic parameters, and forming a short-time energy frequency value sequence; analyzing the short-time energy frequency value sequence from the data of the first frame, and seeking for a pair of voice starting point and ending point; analyzing background noise, and if the background noise is changed, recalculating the audio characteristic parameters of the background noise, and updating the short-time energy frequency value sequence; and repeating the processes till the detection is finished. The method can carry out voice endpoint detection for the continuous voice under the condition that the background noise is changed frequently so as to improve the voice endpoint detection efficiency under a complex noise background.

Systems and methods are disclosed, especially designed for very compact hardware implementations, to generate random number strings with a high level of entropy at maximum speed. For immediate deployment of software implementations, certain permutations have been introduced to maintain the same level of unpredictability which is more amenable to hi-level software programming, with a small time loss on hardware execution; typically when hardware devices communicate with software implementations. Particular attention has been paid to maintain maximum correlation immunity, and to maximize non-linearity of the output sequence. Good stream ciphers are based on random generators which have a large number of secured internal binary variables, which lead to the page synchronized stream ciphering. The method for parsed page synchronization which is presented is especially valuable for Internet applications, where occasionally frame sequences are often mixed. The large number of internal variables with fast diffusion of individual bits wherein the masked message is fed back into the machine variables is potentially ideal for message authentication procedures.

Sensory input processing apparatus and methods useful for adaptive encoding and decoding of features. In one embodiment, the apparatus receives an input frame having a representation of the object feature, generates a sequence of sub-frames that are displaced from one another (and correspond to different areas within the frame), and encodes the sub-frame sequence into groups of pulses. The patterns of pulses are directed via transmission channels to detection apparatus configured to generate an output pulse upon detecting a predetermined pattern within received groups of pulses that is associated with the feature. Upon detecting a particular pattern, the detection apparatus provides feedback to the displacement module in order to optimize sub-frame displacement for detecting the feature of interest. In another embodiment, the detections apparatus elevates its sensitivity (and/or channel characteristics) to that particular pulse pattern when processing subsequent pulse group inputs, thereby increasing the likelihood of feature detection.

The invention relates to a human body skeleton-based action recognition method. The method is characterized by comprising the following basic steps that: step 1, a continuous skeleton data frame sequence of a person who is executing target actions is obtained from a somatosensory device; step 2, main joint point data which can characterize the actions are screened out from the skeleton data; step 3, action feature values are extracted from the main joint point data and are calculated, and a feature vector sequence of the actions is constructed; step 4, the feature vectors are preprocessed; step 4, the feature vector sequence of an action sample set is saved as an action sample template library; step 6, actions are acquired in real time, the distance value of the feature vector sequence of the actions and the feature vector sequence of all action samples in the template library is calculated by using a dynamic time warping algorithm; and step 7, the actions are classified and recognized. The method of the invention has the advantages of high real-time performance, high robustness, high accuracy and simple and reliable implementation, and is suitable for a real-time action recognition system.

A method for determining parking availability includes receiving video data from a sequence of frames taken from an image capture device that is monitoring a parking area. The method includes determining background and foreground images in an initial frame of the sequence of frames. The method further includes updating the background and foreground images in each of the sequence of frames following the initial frame. The method also includes determining a length of a parking space using the determined background and foreground images. The determining includes computing a pixel distance between a foreground image and one of an adjacent foreground image and an end of the parking area. The determining further includes mapping the pixel distance to an actual distance for estimating the length of the parking space.

An endoscope device obtains tissue information of a desired depth near the tissue surface. A xenon lamp (11) in a light source (4) emits illumination light. A diaphragm (13) controls a quantity of the light that reaches a rotating filter. The rotating filter has an outer sector with a first filter set, and an inner sector with a second filter set. The first filter set outputs frame sequence light having overlapping spectral properties suitable for color reproduction, while the second filter set outputs narrow-band frame sequence light having discrete spectral properties enabling extraction of desired deep tissue information. A condenser lens (16) collects the frame sequence light coming through the rotating filter onto the incident face of a light guide (15). The diaphragm controls the amount of the light reaching the filter depending on which filter set is selected.

Methods, systems and computer-program products for encoding an image so that a portion of the image can be extracted without requiring modification of any of the encoded data. A valid MPEG I-frame sequence is generated from the portion of the image, then fed directly to an MPEG decoder for decompression and display.

A method and a device for encoding/decoding video signals by motion compensated temporal filtering. Blocks of a video frame are encoded/decoded using temporal and spatial correlations according to a scalable Motion Compensated Temporal Filtering (MCTF) scheme. When a video signal is encoded using a scalable MCTF scheme, a reference block of an image block in a frame in a video frame sequence constituting the video signal is searched for in temporally adjacent frames. If a reference block is found, an image difference (pixel-to-pixel difference) of the image block from the reference block is obtained, and the obtained image difference is added to the reference block. If no reference block is found, pixel difference values of the image block are obtained based on at least one pixel adjacent to the image block in the same frame. Thus, the encoding procedure uses the spatial correlation between image blocks, improving the coding efficiency.

Systems, methods and apparatuses are described herein for encoding a plurality of video frame sequences, wherein each video frame sequence corresponds to a different perspective view of the same subject matter. In accordance with various embodiments, the encoding is performed in a hierarchical manner that leverages referencing between frames of different ones of the video frame sequences (so-called “external referencing”), but that also allows for encoded representations of only a subset of the video frame sequences to be provided when less than all sequences are required to support a particular viewing mode of a display system that is capable of displaying the subject matter in a two-dimensional mode, a three-dimensional mode, or a multi-view three-dimensional mode.

A method and apparatus inserts virtual advertisements or other virtual contents into a sequence of frames of a video presentation by performing real-time content-based video frame processing to identify suitable locations in the video for implantation. Such locations correspond to both the temporal segments within the video presentation and the regions within an image frame that are commonly considered to be of lesser relevance to the viewers of the video presentation. This invention presents a method and apparatus that allows a non-intrusive means to incorporate additional virtual content into a video presentation, facilitating an additional channel of communications to enhance greater video interactivity.