人们搜索城市户外场所时，不仅依据类别或功能，还关注场所所能支持的活动及其主观感知体验。现有地理空间检索方法仍以兴趣点（POI）为中心、依赖元数据，难以满足开放性、情感化或活动导向的检索需求。本文提出 PlaceSeek——一种以人为中心的户外场所检索框架，可将自然语言查询映射至带地理坐标的街景图像。PlaceSeek 引入一种意图感知的检索机制，将用户查询分解为功能型与情感型子意图；语义定位模块（Semantic Grounding Module）验证候选街景结果是否包含支持目标活动所需的物理证据；情感对齐模块（Affective Alignment Module）则利用在人类城市感知判断数据上经 LoRA 微调的视觉-语言模型，对物理上有效的候选结果进行重排序。我们在米兰 31,956 个街景位置上，针对 5 名人工评估者标注的 10 条自然语言查询对 PlaceSeek 进行评估。结果显示，PlaceSeek 的 Precision@5 达 88.0%，平均匹配得分 3.39/4.0，nDCG@5 为 0.920，性能优于 CLIP、微调后的 CLIP、SigLIP 及基于视觉问答（VQA）的基线方法。消融实验表明，物理定位对检索有效性至关重要，而情感对齐则显著提升物理有效候选结果的排序质量。上述发现表明，复杂的城市空间查询需同时建模可验证的视觉证据与人类感知偏好。PlaceSeek 为下一代以人为中心的地理空间检索系统提供了潜在框架。

People search for urban outdoor places not only by category or function, but also by what activities a place can support and how it is perceived. Existing geospatial retrieval remains largely POIcentric and metadata-driven, making it difficult to satisfy openended, affective, or activity-oriented needs. We present PlaceSeek, a human-centered outdoor place retrieval framework that maps natural-language queries to geolocated street-view imagery. PlaceSeek introduces an intent-aware retrieval mechanism that decomposes user queries into functional and affective sub-intents. A Semantic Grounding Module verifies whether candidate street-view results contain the physical evidence needed to support the intended activity, while an Affective Alignment Module re-ranks physically valid candidates using a LoRA-adapted vision-language model trained on human urban perception judgments. We evaluate PlaceSeek on 31,956 street-view locations in Milan across 10 naturallanguage queries annotated by five human evaluators. PlaceSeek achieves 88.0% Precision@5, a mean match score of 3.39/4.0, and 0.920 nDCG@5, outperforming CLIP, fine-tuned CLIP, SigLIP, and a VQA-based baseline. Ablation results show that physical grounding is essential for retrieval validity, while affective alignment improves ranking quality among physically valid candidates. These findings highlight that complex urban spatial queries require modeling both verifiable visual evidence and human perceptual preferences. PlaceSeek provides a potential framework for human-centered nextgeneration geospatial retrieval systems.