6 results about "Perceptual coding" patented technology

An automatic detection method for CBCT cephalometric landmarks based on multi-geometric guidance and specific perceptual coding includes the following steps: Step S1, downsampling the 3D CBCT image and obtaining a preliminary coordinate set through a coarse localization network; Step S2, cropping image blocks centered on the coordinates and extracting local features through a visual encoder containing a shared basic encoder and a low-rank adapter; Step S3, calculating the relative position matrix of the landmarks, encoding spatial relationships using radial basis functions, and constructing a multi-anatomical heterogeneous map; Step S4, inputting visual and edge features into a multi-geometric guidance Transformer, fusing global constraints and updating features using an attention mechanism; Step S5, extracting directional geometric relationships using spherical harmonic functions to construct higher-order update terms, and dynamically updating the heterogeneous map using a gated residual mechanism; Step S6, predicting coordinate offsets through a multi-layer network and performing iterative optimization to output high-precision 3D coordinates. This method significantly improves detection accuracy and robustness.

The application discloses a light field image perceptual coding method based on intra coding tree unit level code rate allocation, which firstly selects part of sub-aperture images in a sub-aperture image array and arranges the part of sub-aperture images into a pseudo video sequence; then obtains a depth map and a saliency map of a center sub-aperture image by using a depth estimation network and a saliency detection network; then calculates a code rate allocation weight of each coding tree unit in the selected sub-aperture image by using the center sub-aperture image, the depth map and the saliency map, and performs target code rate allocation by using the code rate allocation weight; finally, synthesizes a sub-aperture image which is not selected by using a light field angle super-resolution reconstruction network, and combines the sub-aperture image with a decoded sub-aperture image to form a complete decoded light field image; the method has the advantages that perceptual redundancy existing in the light field image is effectively removed, and the visual quality and structural consistency of a salient region can be maintained at a lower code rate.

This invention relates to the field of edge-cloud collaboration technology, specifically to an emergency rescue video call system and method for people trapped in malfunctioning elevators. The system includes: a state-aware coding module that calculates the signal-to-noise ratio slope to compress macroblocks and construct a video stream; a keyframe loss assessment module that calculates packet loss density to obtain truncation loss rate; an asymmetric error correction scheduling module that stretches the step size to construct a hybrid stream; a delay mapping retransmission module that monitors delay parameters to obtain detection results; and a cross-modal time-domain synchronization module that stretches audio and shifts and calibrates time markers. In this invention, spatial redundancy compression is performed based on dynamic image and signal-to-noise ratio patterns to adapt to physical channel attenuation. The load missing density is analyzed and the step distance is dynamically stretched to perform asymmetric error correction scheduling. Combined with the delay detection results, periodic peak search and non-modulation extension are performed on the waveform to drive the retransmission packet marker shift calibration. In a weak network transmission environment, the audio-visual data is kept aligned in the time domain and the screen stuttering and disconnection faults are eliminated.

An immersive video perception transmission method based on implicit ensemble viewport prediction and representation learning-based bitrate decision-making is proposed, relating to the fields of immersive video transmission and intelligent content-aware coding optimization. To address the problems of insufficient generalization in viewport prediction, non-adaptive user preference modeling, and poor stability under network disturbances in existing technologies, this method establishes an implicit ensemble viewport prediction model with a multi-input / output structure by collecting user head motion trajectory and field-of-view heatmap data; it constructs a bitrate decision engine with mutual information constraints by combining representation learning and reinforcement learning, and achieves tile-level dynamic bitrate allocation based on prediction results and user preferences; it introduces an adversarial training mechanism against bandwidth jitter and packet loss disturbances to enhance robustness; and it adopts a collaborative deployment of cloud, edge, and terminal to achieve end-to-end adaptive optimization. This method is suitable for high-bandwidth, low-latency scenarios, significantly saving bandwidth and improving user experience continuity while ensuring the clarity of the core view area.

The application discloses a kind of perception neuron circuits based on memristor and application, belong to intelligent perception technical field;Integrated perception neuron array is constructed by word line and bit line, and each perception neuron in array is converted into pulse signal and is output in parallel with its perceived external environment information;Each perception neuron in array includes series resistance sensor and threshold transition type memristor;Sensor acts as adjustable resistance, so that memristor works in local active area and normally pulse firing, play the role of sensing environmental information and voltage division, also reduce the difference between devices and devices of multiple perception circuit integration memristor caused by encoding error of perception encoding circuit.In addition, the parasitic capacitance of memristor itself acts as necessary capacitor in memristor neuron circuit;Through the above design, the perception neuron circuit is more compact, greatly improves the integration density, and the reduction of area and hardware saving also reduces energy consumption, improves energy efficiency.