Abstract: In an embodiment, digital video frames in a flow are subjected to a method of extraction of features including the operations of: extracting from the video frames respective sequences of pairs of keypoints/descriptors limiting to a threshold value the number of pairs extracted for each frame; sending the sequences extracted from an extractor module to a server for processing with a bitrate value variable in time; receiving the aforesaid bitrate value variable in time at the extractor as target bitrate for extraction; and limiting the number of pairs extracted by the extractor to a threshold value variable in time as a function of the target bitrate.

Abstract: Image-processing apparatus and methods to adaptively vary an interest point threshold value and control a number of interest points identified in an image frame are described. Sub-regions of an image frame may be processed in a sequence, and an interest point threshold value calculated for each sub-region. The calculated value of the interest point threshold may depend upon pre-selected values and values determined from the processing of one or more prior sub-regions. By using adaptive thresholding, a number of interest points detected for each frame in a sequence of image frames may remain substantially constant, even though objects within the frames may vary appreciably.

Abstract: Local descriptors are extracted from digital image information and digital depth information related to digital images. The local descriptors convey appearance description information and shape description information related to the digital images. Global representations of the one or more digital images are generated based on the extracted local descriptors, and are hashed. Visual search queries are generated based on the hashed global representations. The visual search queries include fused appearance description information and shape description information conveyed in the local descriptors. The fusing may occur before the global representations are generated, before the hashing or after the hashing.

Abstract: In an embodiment, digital video frames in a flow are subjected to a method of extraction of features including the operations of: extracting from the video frames respective sequences of pairs of keypoints/descriptors limiting to a threshold value the number of pairs extracted for each frame; sending the sequences extracted from an extractor module to a server for processing with a bitrate value variable in time; receiving the aforesaid bitrate value variable in time at the extractor as target bitrate for extraction; and limiting the number of pairs extracted by the extractor to a threshold value variable in time as a function of the target bitrate.

Abstract: Image-processing apparatus and methods to adaptively control a size and/or location of a visual search window used for feature matching in a machine-vision system are described. A search window controller may receive motion vector data and image recognition rate data, and compute a search window size and/or search window location based on the received data. The computed search window size may be a portion of an image frame. The motion vector data and image recognition rate data may be computed from one or more images in a video image sequence. By adaptively controlling search window size and location, an appreciable reduction in data processing burden for feature matching may be achieved.

Abstract: Compact descriptors of digital images are produced by detecting interest points representative of the digital images and selecting out of the interest points key points for producing e.g. local and global compact descriptors of the images. The digital images are decomposed into blocks by computing an energy (variance) for each said block and then subjecting the blocks to culling by rejecting those blocks having an energy failing to pass an energy threshold. The interest points are detected only in the blocks resulting from culling, and the key points for producing the compact descriptors are selected out of the interest points thus detected, possibly by using different selection thresholds for local and global compact descriptors, respectively. The number of key points for producing the compact descriptors may be varied e.g. by adaptively varying the number of the interest points detected in the blocks resulting from culling.

Abstract: Digital image processing circuitry clusters a set of images into a set of first clusters of images and a set of unclustered images. The set of first clusters are merged, generating a set of second clusters of images. Images in the set of unclustered images are assigned to one of a cluster of the set of second clusters of images and an outlier image cluster. The clustered images may be partitioned into subclusters based on detection of objects in the images.

Abstract: An image processing system includes a first processor that acquires frames of image data. For each frame of data, the first processor generates a Gaussian pyramid for the frame of data, extract histogram of oriented gradient (HOG) descriptors for each level of the Gaussian pyramid, compresses the HOG descriptors, and sends the compressed HOG descriptors. A second processor is coupled to the first processor and is configured to receive the compressed HOG descriptors, aggregate the compressed HOG descriptors into windows, compare data of each window to at least one stored model, and generate output based upon the comparison.

Abstract: An embodiment of a method for computing pyramids of input images (I) in a transformed domain, e.g., for search and retrieval purposes, includes:—arranging input images in blocks to produce input image blocks,—subjecting the input image blocks to block processing including: transform into a transformed domain, subjecting the image blocks transformed into a transformed domain to filtering, subjecting the image blocks transformed into a transformed domain and filtered to inverse transform implementing an inverse transform with respect to the previous transform into a transformed domain, thus producing a set of processed blocks. The set of processed blocks, which is recomposeable to an image pyramid, may be used, e.g., in detecting extrema points in images in the pyramid, extracting a patch of given size around the extrema points detected, and processing the patch to obtain local descriptors such as SIFT descriptors of a feature.

Abstract: An embodiment of a visual search system includes at least one imaging device, each imaging device operable to capture a corresponding image, a feature extraction device coupled to each imaging device, each feature extraction device operable to generate feature descriptors from the image received from the corresponding imaging device. A descriptor encoding device is coupled to each feature extraction device and operable to generate compressed feature descriptors from the received feature descriptors. An application processor is coupled to each descriptor encoding device. The application processor is operable to process the received compressed feature descriptors to generate output information as a function of the processed compressed feature descriptors.

Abstract: One embodiment is a method for selecting and grouping key points extracted by applying a feature detector on a scene being analyzed. The method includes grouping the extracted key points into clusters that enforce a geometric relation between members of a cluster, scoring and sorting the clusters, identifying and discarding clusters that are comprised of points which represent the background noise of the image, and sub-sampling the remaining clusters to provide a smaller number of key points for the scene.

Abstract: An embodiment is a method for detecting image features, the method including extracting a stripe from a digital image, the stripe including of a plurality of blocks; processing the plurality of blocks for localizing one or more keypoints; and detecting one or more image features based on the one or more localized keypoints.

Abstract: The mass of an object may be estimated based on intersection points of a representation of a surface in an image space with cubes defining the image space, the surface representing a surface of an object. The representation may be, for example, based on marching cubes. The mass may be estimated by estimating a mass contribution of a first set of cubes contained entirely within the representation of the surface, estimating a mass contribution of a second set of cubes having intersection points with the representation of the surface, and summing the estimated mass contribution of the first set of cubes and the estimated mass contribution of the second set of cubes. The object may be segmented from other portions of an image prior to estimating the mass of the object.

Abstract: Disclosed embodiments are directed to methods, systems, and circuits of generating compact descriptors for transmission over a communications network. A method according to one embodiment includes receiving an uncompressed descriptor, performing zero-thresholding on the uncompressed descriptor to generate a zero-threshold-delimited descriptor, quantizing the zero-threshold-delimited descriptor to generate a quantized descriptor, and coding the quantized descriptor to generate a compact descriptor for transmission over a communications network. The uncompressed and compact descriptors may be 3D descriptors, such as where the uncompressed descriptor is a SHOT descriptor. The operation of coding can be ZeroFlag coding, ExpGolomb coding, or Arithmetic coding, for example.

Abstract: Searches performed in a data base using image descriptors of query images are managed via a mobile communication device, such as a smartphone, a tablet, etc., by: extracting at the mobile device grayscale and color descriptors of query images, sending the grayscale descriptors as compressed grayscale descriptors of query images from the mobile device to a server for searching in the data base, receiving at the mobile device results of the search, using color descriptors of query images in disambiguating the results by: i) sending the color descriptors as compressed color descriptors of query images from the mobile device to the server and receiving at the mobile device disambiguated search results from the server, or ii) receiving at the mobile device non-disambiguated search results from the server and disambiguating the search results by means of the color descriptors extracted at the mobile device to produce disambiguated search results.

Abstract: Compact descriptors of digital images are produced by detecting interest points representative of the digital images and selecting out of the interest points key points for producing e.g. local and global compact descriptors of the images. The digital images are decomposed into blocks by computing an energy (variance) for each said block and then subjecting the blocks to culling by rejecting those blocks having an energy failing to pass an energy threshold. The interest points are detected only in the blocks resulting from culling, and the key points for producing the compact descriptors are selected out of the interest points thus detected, possibly by using different selection thresholds for local and global compact descriptors, respectively. The number of key points for producing the compact descriptors may be varied e.g. by adaptively varying the number of the interest points detected in the blocks resulting from culling.

Abstract: An embodiment of a method for computing pyramids of input images (I) in a transformed domain, e.g., for search and retrieval purposes, includes:—arranging input images in blocks to produce input image blocks,—subjecting the input image blocks to block processing including: transform into a transformed domain, subjecting the image blocks transformed into a transformed domain to filtering, subjecting the image blocks transformed into a transformed domain and filtered to inverse transform implementing an inverse transform with respect to the previous transform into a transformed domain, thus producing a set of processed blocks. The set of processed blocks, which is recomposeable to an image pyramid, may be used, e.g., in detecting extrema points in images in the pyramid, extracting a patch of given size around the extrema points detected, and processing the patch to obtain local descriptors such as SIFT descriptors of a feature.

Abstract: A first video frame and a second video frame in a flow of digital video frames are encoded by extracting for the frames in question respective sets of keypoints and descriptors, with each descriptor including a plurality of orientation histograms regarding a patch of pixels centred on the respective keypoint. Once a pair of linked descriptors has been identified, one for the first frame and one for the second frame, which have a minimum distance from among the distances between any one of the descriptors of the first frame and any one of the descriptors of the second frame, the differences of the histograms of the descriptors linked in said pair are calculated, and the descriptors linked in said pair are encoded as the set including one of the linked descriptors and the aforesaid histogram differences by subjecting the histogram differences to a thesholding setting at zero all the differences below a certain threshold, to quantization, and to an encoding of a run-length type.

Abstract: In an embodiment, digital video frames in a flow are subjected to a method of extraction of features including the operations of: extracting from the video frames respective sequences of pairs of keypoints/descriptors limiting to a threshold value the number of pairs extracted for each frame; sending the sequences extracted from an extractor module to a server for processing with a bitrate value variable in time; receiving the aforesaid bitrate value variable in time at the extractor as target bitrate for extraction; and limiting the number of pairs extracted by the extractor to a threshold value variable in time as a function of the target bitrate.

Abstract: Image-processing apparatus and methods to adaptively control a size and/or location of a visual search window used for feature matching in a machine-vision system are described. A search window controller may receive motion vector data and image recognition rate data, and compute a search window size and/or search window location based on the received data. The computed search window size may be a portion of an image frame. The motion vector data and image recognition rate data may be computed from one or more images in a video image sequence. By adaptively controlling search window size and location, an appreciable reduction in data processing burden for feature matching may be achieved.