Television System Details TRIZ Cases

Standardized lighting, camera settings, and machine-learning feedback help on-site booths deliver cohesive photos without photographer coordination.

Fixed-rate structured-light projection can wait on worst-case event retrieval; adaptive timing raises average projection rate for 3D reconstruction.

Motion type and variation guide stabilization and frame fusion, reducing excessive crop while retaining a wider field of view in captured media.

Position and inspection information travel with coded frames to detect tampering even when moving-image streams are divided across files.

Live-view object information matches sound-source metadata, reducing manual search and download steps during video recording.

Users can mark a sample scene while the system selects a recognition unit automatically, improving cutting accuracy without manual engine and rule setup.

An imaging sensor buffers high-resolution frames, then creates slow-motion video and still images from the same sequence for precise synchronization.

Displaying aligned views of the same location from different dates helps users compare wide-view images without confusion from curved imagery.

A detachable rear bracket stores display peripherals behind the back cover while keeping the screen close to the wall.

Multiple nearby user devices capture distant objects from suitable positions and orientations, overcoming single-camera line-of-sight limits.

Detects faces and electronic whiteboards in wide-angle images, then displays a unified view to improve conference record completeness.

Automatic preference learning analyzes captured image classes and recommends edited images, reducing repetitive manual editing on electronic devices.

Ultra-wideband ranging and computer vision align camera positions so physical and virtual frames composite accurately in mixed reality.

Viewer inputs such as tips become control commands that adjust camera functions in near real time, increasing interaction and immersion.

An STB application guides users through device selection, brand entry, and automatic code testing for universal remote setup.

An AV receiver switches encryption settings without rebooting, filtering HDCP content from display output in unencrypted mode.

Subject detection against predefined frame-rate regions simplifies frame-rate adjustment for important scenes during shooting and playback.

Multiple imaging devices and rotation processing place subjects in a safe image zone, preventing edge cutoffs in 360-degree output.

An integrated receiver reduces manual switching by combining TV broadcast decoding with automatic videophone mode transitions.

Eutectic dimples formed during bond-ring etching roughen MEMS movable elements and reduce adhesion to the cap structure.

Segmented audio, video, and marking data are transmitted with slide and time information for synchronized playback on constrained networks.

Detection information activates a second sensor only when an object is detected, reducing power, computation, memory use, and bus traffic.

Audio latency measured by the reproduction equipment is returned over a communication link to align video automatically during playback.

Local enlargement keeps the full scene and critical details visible, then synthesizes both captured views into one target image.

Metadata is prioritized within each frame before demosaicing to limit output delay and preserve high-data-rate recording without added capacity.

Different exposure times address limited sensor dynamic range, while in-sensor linearization merges images and reduces processor load for real-time HDR.

Discrete pixel grids can miss subtle movements and raise processing costs; continuous coordinates improve motion precision without full-image supersampling.

Microlouver film blocks projected content from the rear camera while a reflective layer maintains brightness for clear user video.

Graphical overlays guide multi-angle ground-level photos, improving texture and geometry quality for cost-effective 3D building models.

Machine-learning models tag digital elements across footage, enabling simultaneous post-production and reducing manual rotoscoping labor.

Apply filters, accessories, and borders with adjustable intensity during live video sessions to improve comfort and encourage video participation.

Live detection and segmentation remove selected objects before capture, using scene context for photorealistic fills and avoiding post-capture editing.

A terminal combines sensor IDs, readings, and detection timing from multiple sensors to support consistent processing across fields.

Segmented, state-aware control panels simplify multi-camera capture while time-based metadata synchronizes streams for editing and publishing.

Time-division display and camera-specific replacement keep virtual-production backgrounds natural across multiple viewpoints.

Frequency-modulated light and synchronous detection separate multiple optical-resonator signals without complex wavelength demultiplexing.

A selectable in-call control starts video conferencing without immediately ending the audio call, then completes the transition to exchanged audio and video.

User authentication automatically selects pre-recorded eye-gaze characteristics, reducing repeated calibration and manual choice for multi-user input.

Generative AI uses conference input to create contextually relevant background images, enabling seamless updates without disrupting participants.

Viewer feedback identifies relevant cameras and drives orientation-matched notifications that guide the subject’s gaze during multi-view capture.

Marker detection and perspective morphing place profile-selected ads into existing video streams without proprietary sub-streams.

Generative AI creates one context-aware virtual background across participant video streams without disrupting a live conference.

Controlled delays align diverse conference video inputs with a produced stream, balancing synchronized playback against processing latency.

Proxy media lets less powerful devices review and edit high-definition content while limiting bandwidth use before final replacement.

Received camera time information timestamps microphone audio, linking separately recorded files and simplifying audio-image editing.

Camera and wearable-sensor tracking overcomes depth-perception and field-of-view limits for real-time offside decisions and visualization.

A category setting screen and learning data accumulator let operators label events so video analysis can improve as surveillance conditions change.

Generative AI uses conference transcriptions and topics to update a participant’s virtual background without interrupting discussion.

A coiled cable links primary and auxiliary recorders for independent viewpoints, synchronized data, and more complete incident capture.

The intermediary accessory sends selected audio channels wirelessly and routes video plus remaining channels by wire for synchronized rendering.